痛风的多组学研究进展

痛风是一种由尿酸盐结晶沉积引起的自限性炎症疾病,伴有多种合并症。随着生活水平的提高,痛风在全球的发病率逐年上升,严重影响人民健康。组学技术是研究疾病的有效工具,已被广泛应用于发现痛风的潜在生物标志物和风险因子,其鉴定出的变异位点或差异表达产物为研究痛风的发病机制和疾病进展提供了不同维度的见解和认识。本文通过PubMed检索相关文献,分析和总结了多组学技术在痛风中的应用和研究结果,对近年来多组学技术在痛风领域的相关研究进展进行综述,以期了解痛风患者在不同分子层次上的特异性变化,为今后更深入地研究痛风提供思路和方向。

组学时代下机器学习方法在临床决策支持中的应用

随着组学技术的不断发展,对于不同层次和类型的生物数据的获取方法日益成熟。在疾病诊治过程中会产生大量数据,通过机器学习等人工智能方法解析复杂、多维、多尺度的疾病大数据,构建临床决策支持工具,辅助医生寻找快速且有效的疾病诊疗方案是非常必要的。在此过程中,机器学习等人工智能方法的选择显得尤为重要。基于此,本文首先从类型和算法角度对临床决策支持领域中常用的机器学习等方法进行简要综述,分别介绍了支持向量机、逻辑回归、聚类算法、Bagging、随机森林和深度学习,对机器学习等方法在临床决策支持中的应用做了相应总结和分类,并对它们的优势和不足分别进行讨论和阐述,为临床决策支持中机器学习等人工智能方法的选择提供有效参考。

组学大数据和医学人工智能

随着高通量测序技术和计算机科学的飞速发展,组学数据量指数倍增长,多组学分析优势逐渐显现,人工智能应用也愈加广泛。本文介绍了近年来多组学数据分析和人工智能各自在医学领域的应用进展,同时也介绍了两者相结合应用的案例以及优势,最后简单阐述多组学分析和人工智能在现阶段面临的挑战,旨在为医学行业提供新的研究思路,助推精准医学发展应用。

A Brief Review on the Human Encyclopedia of DNA Elements (ENCODE) Project

The ENCyclopedia Of DNA Elements （ENCODE） project is an international research consortium that aims to identify all functional elements in the human genome sequence. The second phase of the project comprised 1640 datasets from 147 different cell types, yielding a set of 30 publications across several journals. These data revealed that 80.4% of the human genome displays some functionality in at least one cell type. Many of these regulatory elements are physically asso- ciated with one another and further form a network or three-dimensional conformation to affect gene expression. These elements are also related to sequence variants associated with diseases or traits. All these findings provide us new insights into the organization and regulation of genes and genome, and serve as an expansive resource for understanding human health and disease.

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome

To unravel the genetic mechanisms of disease and physiological traits,it requires comprehensive sequencing analysis of large sample size in Chinese populations.Here,we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative(CASPMI)project launched by the Chinese Academy of Sciences,including the de novo assembly of a northern Han reference genome(NH1.0)and whole genome analyses of 597 healthy people coming from most areas in China.Given the two existing reference genomes for Han Chinese(YH and HX1)were both from the south,we constructed NH1.0,a new reference genome from a northern individual,by combining the sequencing strategies of PacBio,10×Genomics,and Bionano mapping.Using this integrated approach,we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1.In order to generate a genomic variation map of Chinese populations,we performed the whole-genome sequencing of 597 participants and identified 24.85 million(M)single nucleotide variants(SNVs),3.85 M small indels,and 106,382 structural variations.In the association analysis with collected phenotypes,we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males.Moreover,significant genetic diversity in MTHFR,TCN2,FADS1,and FADS2,which associate with circulating folate,vitamin B12,or lipid metabolism,was observed between northerners and southerners.Especially,for the homocysteine-increasing allele of rs1801133(MTHFR 677T),we hypothesize that there exists a “comfort”zone for a high frequency of 677T between latitudes of 35–45 degree North.Taken together,our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine.

Databases and Web Tools for Cancer Genomics Study

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community.

Common Postzygotic Mutational Signatures in Healthy Adult Tissues Related to Embryonic Hypoxia

Postzygotic mutations are acquired in normal tissues throughout an individual’s lifetime and hold clues for identifying mutagenic factors.Here,we investigated postzygotic mutation spectra of healthy individuals using optimized ultra-deep exome sequencing of the time-series samples from the same volunteer as well as the samples from different individuals.In blood,sperm,and muscle cells,we resolved three common types of mutational signatures.Signatures A and B represent clocklike mutational processes,and the polymorphisms of epigenetic regulation genes influence the proportion of signature B in mutation profiles.Notably,signature C,characterized by C>T transitions at GpCpN sites,tends to be a feature of diverse normal tissues.Mutations of this type are likely to occur early during embryonic development,supported by their relatively high allelic frequencies,presence in multiple tissues,and decrease in occurrence with age.Almost none of the public datasets for tumors feature this signature,except for 19.6%of samples of clear cell renal cell carcinoma with increased activation of the hypoxia-inducible factor 1(HIF-1)signaling pathway.Moreover,the accumulation of signature C in the mutation profile was accelerated in a human embryonic stem cell line with drug-induced activation of HIF-1α.Thus,embryonic hypoxia may explain this novel signature across multiple normal tissues.Our study suggests that hypoxic condition in an early stage of embryonic development is a crucial factor inducing C>T transitions at GpCpN sites;and individuals’genetic background may also influence their postzygotic mutation profiles.

Strand-biased Gene Distribution in Bacteria Is Related to both Horizontal Gene Transfer and Strand-biased Nucleotide Composition

Although strand-biased gene distribution （SGD） was described some two decades ago, the underlying molecular mechanisms and their relationship remain elusive. Its facets include, but are not limited to, the degree of biases, the strand-preference of genes, and the influence of background nucleotide composition variations. Using a dataset composed of 364 non-redundant bacterial genomes, we sought to illus- trate our current understanding of SGD. First, when we divided the collection of bacterial genomes into non-polC and polC groups according to their possession of DnaE isoforms that correlate closely with taxonomy, the SGD of the polC group stood out more sig- nificantly than that of the non-polC group. Second, when examining horizontal gene transfer, coupled with gene functional conservation （essentiality） and expressivity （level of expression）, we realized that they all contributed to SGD. Third, we further demonstrated a weaker G-dominance on the leading strand of the non-polC group but strong purine dominance （both G and A） on the leading strand of the polC group. We propose that strand-biased nucleotide composition plays a decisive role for SGD since the polC-bearing genomes are not only AT-rich but also have pronounced purine-rich leading strands, and we believe that a special mutation spectrum that leads to a strong purine asymmetry and a strong strand-biased nucleotide composition coupled with functional selections for genes and their functions are both at work.

Big Data and the Brain: Peeking at the Future

The era of brain science across the world The human brain is the most complex organ in the human body.It comprises billions of neurons and supporting cells in a complex network,managing everything from physical functions to thoughts and feelings of humans.Dysfunctions of the complex network caused by both genetic and environmental factors result in many brain disorders.Several large brain projects have been launched,aiming to understand how the brain works in health and disease,including the Human Brain Project of the European Union,the Brain Research through Advancing Innovative Neurotechnologies(BRAIN)Initiative of the United States,and the Brain Mapping by Integrated Neurotechnologies for Disease Studies(Brain/MIND)project of Japan.

GliomaDB: A Web Server for Integrating Glioma Omics Data and Interactive Analysis

Gliomas are one of the most common types of brain cancers.Numerous efforts have been devoted to studying the mechanisms of glioma genesis and identifying biomarkers for diagnosis and treatment.To help further investigations,we present a comprehensive database named GliomaDB.GliomaDB includes 21,086 samples from 4303 patients and integrates genomic,transcriptomic,epigenomic,clinical,and gene-drug association data regarding glioblastoma multiforme(GBM)and low-grade glioma(LGG)from The Cancer Genome Atlas(TCGA),Gene Expression Omnibus(GEO),the Chinese Glioma Genome Atlas(CGGA),the Memorial Sloan Kettering Cancer Center Integrated Mutation Profiling of Actionable Cancer Targets(MSK-IMPACT),the US Food and Drug Administration(FDA),and Pharm GKB.GliomaDB offers a user-friendly interface for two main types of functionalities.The first comprises queries of(i)somatic mutations,(ii)gene expression,(iii)microRNA(miRNA)expression,and(iv)DNA methylation.In addition,queries can be executed at the gene,region,and base level.Second,GliomaDB allows users to perform survival analysis,coexpression network visualization,multi-omics data visualization,and targeted drug recommendations based on personalized variations.GliomaDB bridges the gap between glioma genomics big data and the delivery of integrated information for end users,thus enabling both researchers and clinicians to effectively use publicly available data and empowering the progression of precision medicine in glioma.GliomaDB is freely accessible at http://bigd.big.ac.cn/glioma DB.

Long noncoding RNA PCED1B-AS1 promotes erythroid differentiation coordinating with GATA1 and chromatin remodeling

Erythropoiesis is a complex and sophisticated multi-stage process regulated by a variety of factors,including the transcription factor GATA1 and non-coding RNA.GATA1 is regarded as an essential transcriptional regulator promoting transcription of erythroidspecific genes—such as long non-coding RNAs(lncRNA).Here,we comprehensively screened lncRNAs that were potentially regulated by GATA1 in erythroid cells.We identified a novel lncRNA—PCED1B-AS1—and verified its role in promoting erythroid differentiation of K562 erythroid cells.We also predicted a model in which PCED1B-AS1 participates in erythroid differentiation via dynamic chromatin remodeling involving GATA1.The relationship between lncRNA and chromatin in the process of erythroid differentiation remains to be revealed,and in our study we have carried out preliminary explorations.

Biological Databases for Hematology Research

With the advances of genome-wide sequencing technologies and bioinformatics approaches, a large number of datasets of normal and malignant erythropoiesis have been gener- ated and made public to researchers around the world. Collection and integration of these datasets greatly facilitate basic research and clinical diagnosis and treatment of blood disorders. Here we provide a brief introduction of the most popular omics data resources of normal and malignant hematopoiesis, including some integrated web tools, to help users get better equipped to perform common analyses. We hope this review will promote the awareness and facilitate the usage of public