中医药文献语义标注系统研究与开发

目的研究和开发支持中医和现代生物医学本体和术语集的语义标注系统。方法以MedPortal本体库和中医临床术语集等为术语资源库,设计语义标注系统工作流程和功能框架,并开发Web应用系统。结果构建了一个基于Web的中医药文献语义标注系统,支持语料库管理与维护、术语词典管理、语义标注和语义检索等功能,既可以为基于机器学习的信息抽取算法研究提供训练集,又能实现语义层面的多来源数据集成与知识融合。结论该中医药文献语义标注系统设计方案已经过实际项目验证,可为其他同类系统研发提供参考。     

SimPEL: Simulation‐based power estimation for sequencing studies of low‐prevalence conditions

Power estimations are important for optimizing genotype‐phenotype association study designs. However, existing frameworks are designed for common disorders, and thus ill‐suited for the inherent challenges of studies for low‐prevalence conditions such as rare diseases and infrequent adverse drug reactions. These challenges include small sample sizes and the need to leverage genetic annotation resources in association analyses for the purpose of ranking potential causal genes. We present SimPEL, a simulation‐based program providing power estimations for the design of low‐prevalence condition studies. SimPEL integrates the usage of gene annotation resources for association analyses. Customizable parameters, including the penetrance of the putative causal allele and the employed pathogenic scoring system, allow SimPEL to realistically model a large range of study designs. To demonstrate the effects of various parameters on power, we estimated the power of several simulated designs using SimPEL and captured power trends in agreement with observations from current literature on low‐frequency condition studies. SimPEL, as a tool, provides researchers studying low‐frequency conditions with an intuitive and highly flexible avenue for statistical power estimation. The platform‐independent “batteries included” executable and default input files are available at https://github.com/precisionomics/SimPEL .     

RNA-Seq analysis in an avian model of maternal phenylketonuria

Cardiac malformations (CVMs) are a leading cause of infant morbidity and mortality. CVMs are particularly prevalent when the developing fetus is exposed to high levels of phenylalanine in-utero in mothers with Phenylketonuria. Yet, elucidating the underlying molecular mechanism leading to CVMs has proven difficult. In this study we used RNA-Seq to investigate an avian model of MPKU and establish differential gene expression (DEG) characteristics of the early developmental stages HH10, 12, and 14. In total, we identified 633 significantly differentially expressed genes across stages HH10, 12, and 14. As expected, functional annotation of significant DEGs identified associations seen in clinical phenotypes of MPKU including CVMs, congenital heart defects, craniofacial anomalies, central nervous system defects, and growth anomalies. Additionally, there was an overrepresentation of genes involved in cardiac muscle contraction, adrenergic signaling in cardiomyocytes, migration, proliferation, metabolism, and cell survival. Strikingly, we identified significant changes in expression with multiple genes involved in Retinoic Acid (RA) metabolism and downstream targets. Using qRTPCR, we validated these findings and identified a total of 42 genes within the RA pathway that are differentially expressed. Here, we report the first elucidation of the molecular mechanisms of cardiovascular malformations in MPKU conducted at early developmental timepoints. We provide evidence suggesting a link between PHE exposure and the alteration of RA pathway. These results are promising and offer novel findings associated with congenital heart defects in MPKU.     

老鸦瓣芽茎发育相关MYB转录因子家族鉴定与分析

目的鉴定老鸦瓣Amana edulis MYB转录因子家族成员并分析其表达模式,以期发现老鸦瓣芽茎发育相关MYB基因。方法利用老鸦瓣转录组数据经Pfam和PlnTFDB数据库鉴定含有MYB保守结构域的MYB转录因子,通过构建系统进化树并根据拟南芥MYB分组信息为老鸦瓣R2R3-MYB基因划分亚组,进行2R-MYB结构域可视化分析和GO富集分析,挑选在芽茎中特异表达的MYB基因并用实时荧光定量PCR(qRT-PCR)验证表达。结果共鉴定出93个含有MYB保守结构域的MYB转录因子,其中53个R2R3-MYB分为15个亚组,GO注释为生物过程的子类别最多,在芽茎中特异表达的12个MYB基因中有11个基因在芽茎发育前期至中期的表达量显著下降,有4个基因在芽茎发育中期至后期的表达量显著上升。结论获得的53个R2R3-MYB转录因子为进一步研究老鸦瓣MYB转录因子家族影响芽茎发育过程的分子机制奠定了基础。     

基于网络药理学探讨小青龙汤治疗慢性阻塞性肺疾病的作用机制

目的：利用网络药理学分析小青龙汤治疗慢性阻塞性肺疾病（COPD）的作用机制。方法：在中药系统药理学数据库与分析平台（TCMSP）检索小青龙汤药物活性成分和靶点,绘制中药-化合物-靶基因网络,筛选关键化合物;利用GeneCards和人类孟德尔遗传数据库（OMIM）搜索COPD疾病基因;绘制韦恩图并获取药物-疾病共同基因;利用小青龙汤-慢阻肺药物疾病共同基因绘制蛋白质-蛋白质相互作用（PPI）网络,根据网络关系选择核心基因;对核心基因分别进行基因本体（GO）功能注释和富集分析和京都基因和基因组百科全书（KEGG）通路富集分析。结果：挖掘得到小青龙汤中药活性成分137个,潜在作用靶点188个,慢性阻塞性肺疾病相关靶点6 949个,小青龙汤-COPD共同靶点160个,主要富集于92个生物过程和49条信号通路上。结论：小青龙汤中多个药物含有山柰酚、槲皮素、（+）-儿茶素、豆甾醇、β-谷固醇等成分,可作用于AKT1、IL6、MAPK1、PTGS2、TP53等核心基因,调控氧化应激反应、血小板α-颗粒等生物过程,参与HIF-1、PI3K-AKT信号通路的调节,干预氧化应激反应和炎症反应等过程,产生抑制炎症反应、抗氧化应激的作用,进而通过上述过程参与COPD的炎症反应与氧化应激过程。     

MSeqDR mvTool: A mitochondrial DNA Web and API resource for comprehensive variant annotation,universal nomenclature collation,and reference genome conversion

Accurate mitochondrial DNA (mtDNA) variant annotation is essential for the clinical diagnosis of diverse human diseases. Substantial challenges to this process include the inconsistency in mtDNA nomenclatures, the existence of multiple reference genomes, and a lack of reference population frequency data. Clinicians need a simple bioinformatics tool that is user‐friendly, and bioinformaticians need a powerful informatics resource for programmatic usage. Here, we report the development and functionality of the MSeqDR mtDNA Variant Tool set (mvTool), a one‐stop mtDNA variant annotation and analysis Web service. mvTool is built upon the MSeqDR infrastructure ( https://mseqdr.org ), with contributions of expert curated data from MITOMAP ( https://www.mitomap.org ) and HmtDB ( https://www.hmtdb.uniba.it/hmdb ). mvTool supports all mtDNA nomenclatures, converts variants to standard rCRS‐ and HGVS‐based nomenclatures, and annotates novel mtDNA variants. Besides generic annotations from dbNSFP and Variant Effect Predictor (VEP), mvTool provides allele frequencies in more than 47,000 germline mitogenomes, and disease and pathogenicity classifications from MSeqDR, Mitomap, HmtDB and ClinVar (Landrum et al., 2013). mvTools also provides mtDNA somatic variants annotations. “mvTool API” is implemented for programmatic access using inputs in VCF, HGVS, or classical mtDNA variant nomenclatures. The results are reported as hyperlinked html tables, JSON, Excel, and VCF formats. MSeqDR mvTool is freely accessible at https://mseqdr.org/mvtool.php .     

Inferring the effect of genomic variation in the new era of genomics

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene‐variant–disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next‐generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as “synergistic heterozygosity,” digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large‐scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.