A normalization strategy for comparing tag count data

Background

High-throughput sequencing, such as ribonucleic acid sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) analyses, enables various features of organisms to be compared through tag counts. Recent studies have demonstrated that the normalization step for RNA-seq data is critical for a more accurate subsequent analysis of differential gene expression. Development of a more robust normalization method is desirable for identifying the true difference in tag count data.

Results

We describe a strategy for normalizing tag count data, focusing on RNA-seq. The key concept is to remove data assigned as potential differentially expressed genes (DEGs) before calculating the normalization factor. Several R packages for identifying DEGs are currently available, and each package uses its own normalization method and gene ranking algorithm. We compared a total of eight package combinations: four R packages (edgeR, DESeq, baySeq, and NBPSeq) with their default normalization settings and with our normalization strategy. Many synthetic datasets under various scenarios were evaluated on the basis of the area under the curve (AUC) as a measure for both sensitivity and specificity. We found that packages using our strategy in the data normalization step overall performed well. This result was also observed for a real experimental dataset.

Conclusion

Our results showed that the elimination of potential DEGs is essential for more accurate normalization of RNA-seq data. The concept of this normalization strategy can widely be applied to other types of tag count data and to microarray data.     

Chromatin Immunoprecipitation (ChIP) using Drosophila tissue

Epigenetics remains a rapidly developing field that studies how the chromatin state contributes to differential gene expression in distinct cell types at different developmental stages. Epigenetic regulation contributes to a broad spectrum of biological processes, including cellular differentiation during embryonic development and homeostasis in adulthood. A critical strategy in epigenetic studies is to examine how various histone modifications and chromatin factors regulate gene expression. To address this, Chromatin Immunoprecipitation (ChIP) is used widely to obtain a snapshot of the association of particular factors with DNA in the cells of interest.ChIP technique commonly uses cultured cells as starting material, which can be obtained in abundance and homogeneity to generate reproducible data. However, there are several caveats: First, the environment to grow cells in Petri dish is different from that in vivo, thus may not reflect the endogenous chromatin state of cells in a living organism. Second, not all types of cells can be cultured ex vivo. There are only a limited number of cell lines, from which people can obtain enough material for ChIP assay.Here we describe a method to do ChIP experiment using Drosophila tissues. The starting material is dissected tissue from a living animal, thus can accurately reflect the endogenous chromatin state. The adaptability of this method with many different types of tissue will allow researchers to address a lot more biologically relevant questions regarding epigenetic regulation in vivo^{1, 2}. Combining this method with high-throughput sequencing (ChIP-seq) will further allow researchers to obtain an epigenomic landscape.     

Experience-dependent neuroplasticity of the developing hypothalamus: integrative epigenomic approaches

Augmented maternal care during the first postnatal week promotes life-long stress resilience and improved memory compared with the outcome of routine rearing conditions. Recent evidence suggests that this programming commences with altered synaptic connectivity of stress sensitive hypothalamic neurons. However, the epigenomic basis of the long-lived consequences is not well understood. Here, we employed whole-genome bisulfite sequencing (WGBS), RNA-sequencing (RNA-seq), and a multiplex microRNA (miRNA) assay to examine the effects of augmented maternal care on DNA cytosine methylation, gene expression, and miRNA expression. A total of 9,439 differentially methylated regions (DMRs) associated with augmented maternal care were identified in male offspring hypothalamus, as well as a modest but significant decrease in global DNA methylation. Differentially methylated and expressed genes were enriched for functions in neurotransmission, neurodevelopment, protein synthesis, and oxidative phosphorylation, as well as known stress response genes. Twenty prioritized genes were identified as highly relevant to the stress resiliency phenotype. This combined unbiased approach enabled the discovery of novel genes and gene pathways that advance our understanding of the epigenomic mechanisms underlying the effects of maternal care on the developing brain.     

Whole-genome chromatin profiling from limited numbers of cells using nano-ChIP-seq

Chromatin immunoprecipitation (ChIP) combined with high-throughput sequencing (ChIP-seq) has become the gold standard for whole-genome mapping of protein-DNA interactions. However, conventional ChIP protocols necessitate the use of large numbers of cells, and library preparation steps associated with current high-throughput sequencing platforms require substantial amounts of DNA; both of these factors preclude the application of ChIP-seq technology to many biologically important but rare cell types. Here we describe a nano-ChIP-seq protocol that combines a high-sensitivity small-scale ChIP assay and a tailored procedure for generating high-throughput sequencing libraries from scarce amounts of ChIP DNA. In terms of the numbers of cells required, the method provides two to three orders of magnitude of improvement over the conventional ChIP-seq method and the entire procedure can be completed within 4 d.     

通过系统分析揭示组蛋白修饰模式与转录因子结合之间的关联

转录因子对顺势调控元件的选择性结合,在哺乳动物细胞类型特异的基因表达中扮演重要的角色.这个过程受到染色质表观遗传状态的潜在调控.近期,染色质免疫共沉淀结合测序的研究提供了大量泛基因组水平的数据,阐述转录因子结合以及组蛋白修饰的位点,这为系统地研究转录因子和表观遗传标记之间的空间及调控关系提供了基础.该研究对公共数据库中的染色质免疫共沉淀结合测序数据进行整合分析,涉及5个细胞系中的85种转录因子、9种组蛋白修饰,目的是研究转录因子结合位点与组蛋白修饰模式以及基因表达在泛基因组水平上的关联.作者发现,不同转录因子与组蛋白修饰的共定位模式高度一致,并且组蛋白修饰在距离转录因子结合位点约500碱基对的位置富集.作者还发现,转录因子结合位点的占有率与活性组蛋白修饰的水平和双峰模式正相关,并且启动子区域组蛋白修饰的双峰和共定位模式和基因的高转录水平相一致.组蛋白修饰模式、转录因子结合位点的占有率与基因转录之间的关联暗示了细胞可能利用的基因表达调控机制.     

多组学大数据整合分析揭示早期胚胎发育过程中基因表达调控信息的变化规律

摘要 目的：探究哺乳动物早期胚胎发育过程中基因表达调控信息的变化规律。方法：收集小鼠早期胚胎发育各时期的RNA-seq,ATAC-seq,MethylC-Seq和H3K4me3 ChIP-seq数据进行整合分析,观察小鼠早期胚胎发育各时期转录因子表达量的变化,计算各时期基因表达量与转录因子结合位点数量及染色质可及性的相关性,筛选各时期表达量前10%的基因,统计其表达量和转录因子占比,并进行启动子可及性分析。根据前期报道的转录因子三节点调控网络,对早期胚胎各时期转录因子调控网络的富集模式进行分析。根据多组学数据分析结果,推测早期胚胎发育调控过程中转录因子和表观遗传修饰信息的共调控模型。结果：转录因子数量和调控关系变化以及染色质可及性、DNA甲基化修饰、组蛋白修饰等表观遗传修饰共同调控早期胚胎发育各时期的基因表达,这些因素在不同时期发挥不同程度的调控作用。结论：转录因子和表观遗传修饰在早期胚胎发育过程中动态调控基因表达。