CpG islands are the second main factor shaping codon usage in human genes

A correspondence analysis of codon usage in human genes revealed, as expected, that the first axis is strongly correlated with the base composition at synonymous third codon positions. At one extreme of the second axis were localized genes with a high frequency of NCG and CGN codons. The great majority of these sequences were embedded in CpG islands, while the opposite is true for the genes placed at the other extreme. The two main conclusions of this paper are: (1) the influence of CpG islands on codon usage, and (2) since the second axis is orthogonal (and therefore independent) of the first, GC3-rich genes are not necessarily associated with CpG islands.     

CpGIF: an algorithm for the identification of CpG islands

CpG islands (CGIs) play a fundamental role in genome analysis and annotation, and contribute to improving the accuracy of promoter prediction. Besides, CGIs in promoter regions are abnormally methylated in cancer cells and thus can be used as tumor markers. However, current methods for identifying CGIs suffer from various drawbacks. We present a new algorithm for detecting CGIs, called CpG Island Finder (CpGIF), which combines the best features in the most commonly used algorithms and avoids their disadvantages as much as possible. Five public tools for CpG island searching are used to compare with CpGIF for the assessment of accuracy and computational efficiency. The results reveal that CpGIF has higher performance coefficient and correlation coefficient than these previous methods, which indicates that CpGIF is able to provide high sensitivity and specificity at the same time. CpGIF is also faster than those methods with comparable prediction accuracy.     

Segmental distribution of genes harboring a CpG island-like region on rice chromosomes

In plant genomes, there exist discrete regions rich in CpG dinucleotides, namely CpG clusters. In rice, most of these CpG clusters are associated with genes. Rice genes are grouped into one of the five classes according to the position of an associated CpG cluster. Among them, class 1 genes, which harbor a CpG cluster at the 5′-terminus, share similarities with human genes having CpG islands. In the present study, by analyzing plant genome sequence data, primarily from rice, we investigated the chromosomal distribution of genes of each class, mainly class 1 genes. Class 1 genes were not uniformly distributed across the rice genome, but were clustered into discrete chromosomal segments. EST-based analysis of the distribution of expressed genes indicates that this segmental distribution of class 1 genes caused a preferential distribution of expressed genes within class 1 gene-rich segments. We then compared the methylation status of genes of each class to examine the possibility that differential DNA methylation, if any, is relevant to the observed differential expression level of genes inside and outside the class 1 segments. The difference in the methylation level between these genes was revealed to be fairly small, which does not support the above-mentioned possibility. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Specific gene hypomethylation and cancer: New insights into coding region feature trends

Giving coding region structural features a role in the hypomethylation of specific genes, the occurrence of G+C content, CpG islands, repeat and retrotransposable elements in demethylated genes related to cancer has been evaluated. A comparative analysis among different cancer types has also been performed. In this work, the inter-cancer coding region features comparative analysis carried out, show insights into what structural trends/patterns are present in the studied cancers.     

Genomic specification and epigenetic regulation of eukaryotic DNA replication origins

Identification of DNA replication origins (ORIs) at a genome-wide level in eukaryotes has proved to be difficult due to the high degree of degeneracy of their sequences. Recent structural and functional approaches, however, have circumvented this limitation and have provided reliable predictions of their genomic distribution in the yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe, and they have also significantly increased the number of characterized ORIs in animals. This article reviews recent evidence on how ORIs are specified and maintained in these systems and on their regulation and sensitivity to epigenetic signals. It also discusses the possible additional involvement of ORIs in processes other than DNA replication.     

结直肠癌中DNA甲基化研究进展

CpG岛是人类基因组中富含CpG二核苷酸的DNA序列,主要位于基因启动子区,大小约为100-1000bp,与约60％编码基因相关。DNA中CpG岛甲基化可导致抑癌基因的表观遗传学转录失活,直接参与肿瘤的发生机制。近年来,甲基化已成为表观遗传学研究的焦点。我们简要综述了DNA甲基化在结直肠癌中的研究进展。     

大豆根瘤菌SCAUs8的接种效果、促生性及系统发育研究

【目的】大豆是我国重要的农作物,利用大豆-根瘤菌共生体系能有效减少化学氮肥的用量。将初筛的大豆根瘤菌SCAUs8在四川两个重要的大豆种植生态区进行田间接种验证试验,同时对该菌株进行分类地位研究。【方法】在四川丘陵区和攀西地区,采用大田试验调查接种大豆根瘤菌SCAUs8对大豆的增产效果。采用点接种法研究SCAUs8的抗逆性,用Salkowski比色法检测供试菌分泌吲哚乙酸(IAA)的能力。用多位点基因(16S r RNA,atp D,rec A,glnⅡ,nod C,nif H)序列分析对供试菌株SCAUs8进行分类地位的确定。【结果】大田试验表明,接种大豆根瘤菌SCAUs8后,大豆植株的产量、鲜重、干重等指标明显高于不接种对照(CK)处理,其中大豆植株产量比不接种CK增产21.4%-29.7%,其差异达显著水平。对供试菌株SCAUs8进行的耐酸碱性、耐盐性、生长温度范围以及分泌IAA能力测定的结果表明,供试菌株SCAUs8能在p H5.0-10.0正常生长,可耐受Na Cl浓度为0.5%,生长温度范围是10-40°C,能分泌IAA。综合16S r RNA、atp D、rec A、glnⅡ、nod C、nif H基因的序列分析,发现供试菌株SCAUs8与Bradyrhizobium diazoefficiens USDA110T相似性高达100%。【结论】供试菌株SCAUs8是与四川主栽大豆品种共生匹配性较好的广谱菌株。该菌株耐盐性较差,但具有较强的耐酸碱性、较宽的生长温度范围及分泌IAA的能力。系统发育研究将供试菌株SCAUs8确定为B.diazoeffciens。     

Gene-associated CpG islands in plants as revealed by analyses of genomic sequences

We screened plant genome sequences, primarily from rice and Arabidopsis thaliana, for CpG islands, and identified DNA segments rich in CpG dinucleotides within these sequences. These CpG-rich clusters appeared in the analysed sequences as discrete peaks and occurred at the frequencies of one per 4.7 kb in rice and one per 4.0 kb in A. thaliana. In rice and A. thaliana, most of the CpG-rich clusters were associated with genes, which suggests that these clusters are useful landmarks in genome sequences for identifying genes in plants with small genomes. In contrast, in plants with larger genomes, only a few of the clusters were associated with genes. These plant CpG-rich clusters satisfied the criteria used for identifying human CpG islands, which suggests that these CpG clusters may be regarded as plant CpG islands. The position of each island relative to the 5'-end of its associated gene varied considerably. Genes in the analysed sequences were grouped into five classes according to the position of the CpG islands within their associated genes. A large proportion of the genes belonged to one of two classes, in which a CpG island occurred near the 5'-end of the gene or covered the whole gene region. The position of a plant CpG island within its associated gene appeared to be related to the extent of tissue-specific expression of the gene; the CpG islands of most of the widely expressed rice genes occurred near the 5'-end of the genes.     

基于统计CPG岛的基因预测方法

随着以功能基因组学和蛋白质组学为主要研究内容的后基因组时代的来临,人们面对着生物信息的数据呈指数增长,如何通过有效的计算方法由核酸和蛋白质的序列推导出它们的结构和功能,特别是识别DNA序列中编码蛋白质的基因预测问题是迫切需要解决的研究课题之一.本文在CpG岛对研究基因编码的特殊生物意义下,通过三种方法确定CpG岛的位置,并在此基础上,结合一种新的DNA序列字母向量,利用信息熵离散量预测基因序列,提高了识别基因编码的效率,而且计算的时间有显著的减少.     

DNA甲基化微阵列

DNA甲基化微阵列是近年发展起来的高通量分析基因组水平DNA甲基化状态和模式的新型技术,已成为肿瘤表观遗传学组研究的重要工具之一。利用DNA甲基化微阵列研究某种疾病状态下异常甲基化的基因有利于进一步明确该疾病的表观遗传学异常机制,发现与之相关的表观遗传学标志物。现有的DNA甲基化微阵列主要包括CpG岛微阵列和甲基化寡聚核苷探针微阵列,根据已有的文献资料,较为详细地阐述了上述技术的原理、特点和适用范围,对于研究者根据自己的研究目的选择适当的DNA甲基化微阵列技术具有一定的指导价值。