Analysis of DNA methylation in different maize tissues

DNA methylation plays an important role in gene expression regulation during biological development and tissue differentiation in plants. This study adopted methylation-sensitive Amplified fragment length polymorphism （AFLP） to compare the levels of DNA cytosine methylation at CCGG sites in tassel, bracteal leaf, and ear leaf from maize inbred lines, 18 White and 18 Red, respectively, and also examined specific methylation patterns of the three tissues. Significant differences in cytosine methylation level among the three tissues and the same changing tendency in two inbred lines were detected. Both MSAP （methylation sensitive amplification polymorphism） ratio and full methylation level were the highest in bracteal leaf, and the lowest in tassel. Meanwhile, different methylation levels were observed in the same tissue from the inbred lines, 18 White and 18 Red. Full methylation of internal cytosine was the dominant type in the maize genome. The differential methylation patterns in the three tissues were observed. In addition, sequencing of nine differentially methylated fragments and the subsequent blast search revealed that the cytosine methylated 5 ＇ -CCGG-3 ＇ sequences were distributed in repeating sequences, in the coding and noncoding regions. Southern hybridization was used to verify the methylation polymorphism. These results clearly demonstrated the power of the MSAP technique for large-scale DNA methylation detection in the maize genome, and the complexity of DNA methylation change during plant growth and development. The different methylation levels may be related to specific gene expression in various tissues.     

应用MSAP方法检测鸡不同组织基因组的甲基化状态

以白洛克肉鸡和白来航蛋鸡及其杂交F1代基因组为实验材料,应用甲基敏感扩增片段多态性方法(Methylation sensitive amplified polymorphism,MSAP)检测了鸡肌肉、心脏、肝脏和肾脏4个不同组织基因组在CCGG位点的甲基化状态,分析了不同组织的DNA甲基化水平及组织特异性甲基化模式。研究发现:肌肉组织的甲基化水平约为29.7%,肝脏组织约为27.5%,心脏组织约为27.5%,肾脏组织约为26.1%;在鸡3个不同群体及其中3个不同组织间,基因组甲基化程度差异显著(P<0.05);在检测的4个组织中,CCGG序列的全甲基化位点少于半甲基化位点,与植物的相关研究不一致;分离及鉴定了2个组织特异的甲基化片段。结果表明:鸡不同组织基因组的甲基化状态是不同的,同一组织的甲基化水平在不同的群体是不同的,而不同组织甲基化水平的排序在不同的群体是不一致的。这些结果揭示遗传效应可能影响个体的组织甲基化水平。     

Bis-class: a new classification tool of methylation status using bayes classifier and local methylation information

Background

Whole genome sequencing of bisulfite converted DNA (‘methylC-seq’) method provides comprehensive information of DNA methylation. An important application of these whole genome methylation maps is classifying each position as a methylated versus non-methylated nucleotide. A widely used current method for this purpose, the so-called binomial method, is intuitive and straightforward, but lacks power when the sequence coverage and the genome-wide methylation level are low. These problems present a particular challenge when analyzing sparsely methylated genomes, such as those of many invertebrates and plants.

Results

We demonstrate that the number of sequence reads per position from methylC-seq data displays a large variance and can be modeled as a shifted negative binomial distribution. We also show that DNA methylation levels of adjacent CpG sites are correlated, and this similarity in local DNA methylation levels extends several kilobases. Taking these observations into account, we propose a new method based on Bayesian classification to infer DNA methylation status while considering the neighborhood DNA methylation levels of a specific site. We show that our approach has higher sensitivity and better classification performance than the binomial method via multiple analyses, including computational simulations, Area Under Curve (AUC) analyses, and improved consistencies across biological replicates. This method is especially advantageous in the analyses of sparsely methylated genomes with low coverage.

Conclusions

Our method improves the existing binomial method for binary methylation calls by utilizing a posterior odds framework and incorporating local methylation information. This method should be widely applicable to the analyses of methylC-seq data from diverse sparsely methylated genomes. Bis-Class and example data are provided at a dedicated website (http://bibs.snu.ac.kr/software/Bisclass).

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-608) contains supplementary material, which is available to authorized users.     

Starch determination in plant tissues using a computerized image analysis system

Starch is the main reserve compound in woody plant species. Changes in starch content are clear indicators of a variety of plant developmental processes. Thus, carbohydrate extraction and other analytical methods have been widely used to measure changes in starch content. However, the use of these methods can be limited by the fact that starch is often compartmentalized in very small portions of tissue. While changes in these small structures can be histochemically characterized and localized under the microscope, they cannot be quantified. As an alternative, an image analysis system attached to a microscope has been developed to detect quantitative variations in starch in particular tissues or cells. The system has been successfully used to study the differences in starch content of sections from pistillar structures in apricot ( Prunus armeniaca L.). The procedure is based on the measurement of the optical density of black and white images obtained from the microscope. Two staining methods, I₂KI (potassium iodide-iodine) and PAS (periodic acid Schiff's reagent), and two embedding techniques, paraffin and JB4 plastic resin, were compared. The best results were obtained using I₂KI-stained sections of paraffin-embedded material. Since the procedures used are non-destructive for the tissues studied, additional information can be obtained, on the same section, by the subsequent use of additional stains. The method described here can be used to detect quantitative variations in starch content under the microscope in different plant tissues and thus to follow changes in starch reserves in small structures.     

Large-scale methylation patterns in the nuclear genomes of plants.

Methylation was investigated in compositional fractions of nuclear DNA preparations (50-100 kb in size) from five plants (onion, maize, rye, pea and tobacco), and was found to increase from GC-poor to GC-rich fractions. This methylation gradient showed different patterns in different plants and appears, therefore, to represent a novel, characteristic genome feature which concerns the noncoding, intergenic sequences that make up the bulk of the plant genomes investigated and mainly consist of repetitive sequences. The structural and functional implications of these results are discussed.     

Quantitative proteome analysis of ovarian cancer tissues using a iTRAQ approach

Quantitative proteomics can be used as a screening tool for identification of differentially expressed proteins as potential biomarkers for cancers. Here, we comparatively analyzed the proteome profiles of ovarian cancer tissues and normal ovarian epithelial tissues. Using the high‐throughput proteomic technology of isobaric tags for relative and absolute quantitation (iTRAQ)‐coupled with two‐dimensional‐liquid chromatography‐tandem mass spectrometry, 1,259 unique proteins were identified. Of those, 205 were potentially differentially expressed between ovarian cancer and normal ovarian tissues. Several of the potentially differentially expressed proteins were validated by Western blotting and real‐time quantitative RT‐PCR analyses. Furthermore, up‐regulation of KRT8, PPA1, IDH2, and S100A11 were validated in ovarian tissue microarrays by immunohistochemistry. Silencing of S100A11 expression suppressed the migration and invasion properties of ovarian cancer cells in vitro. Our study represents the successful application of iTRAQ technology to an investigation of ovarian cancer. Many of the potentially differentially expressed proteins identified had not been linked to ovarian cancer before, and provide valuable novel insights into the underlying mechanisms of carcinogenesis in human ovarian cancer. J. Cell. Biochem. 113: 3762–3772, 2012. © 2012 Wiley Periodicals, Inc.     

Comparative DNA methylation analysis in normal and tumour tissues and in cancer cell lines using differential methylation hybridisation

Immortalized human cancer cell lines are widely used as tools and model systems in cancer research but their authenticity with regard to primary tissues remains a matter of debate. We have used differential methylation hybridisation to obtain comparative methylation profiles from normal and tumour tissues of lung and colon, and permanent cancer cell lines originally derived from these tissues. Average methylation differences only larger than 25% between sample groups were considered for the profiles and with this criterion approximately 1000 probesets, around 2% of the sites represented on the array, indicated differential methylation between normal lung and primary lung cancer tissue, and approximately 700 probesets between normal colon and primary colon cancer tissue. Both hyper- and hypomethylation was found to differentiate normal tissue from cancer tissue. The profiles obtained from these tissue comparisons were found to correspond largely to those from the corresponding cancer cell lines, indicating that the cell lines represent the methylation pattern of the primary tissue rather well. Moreover, the cancer specific profiles were found to be very similar for the two tumour types studied. Tissue specific differential methylation between lung and colon tissues, in contrast, was found to be preserved to a larger extent only in the malignant tissue, but was not preserved well in the cancer cell lines studied. Overall, our data therefore provide further evidence that permanent cell lines are good model systems for cancer specific methylation patterns, but deviate with regard to tissue-specific methylation.     

Random forests, a novel approach for discrimination of fish populations using parasites as biological tags

Due to the complexity of host-parasite relationships, discrimination between fish populations using parasites as biological tags is difficult. This study introduces, to our knowledge for the first time, random forests (RF) as a new modelling technique in the application of parasite community data as biological markers for population assignment of fish. This novel approach is applied to a dataset with a complex structure comprising 763 parasite infracommunities in population samples of Atlantic cod, Gadus morhua, from the spawning/feeding areas in five regions in the North East Atlantic (Baltic, Celtic, Irish and North seas and Icelandic waters). The learning behaviour of RF is evaluated in comparison with two other algorithms applied to class assignment problems, the linear discriminant function analysis (LDA) and artificial neural networks (ANN). The three algorithms are used to develop predictive models applying three cross-validation procedures in a series of experiments (252 models in total). The comparative approach to RF, LDA and ANN algorithms applied to the same datasets demonstrates the competitive potential of RF for developing predictive models since RF exhibited better accuracy of prediction and outperformed LDA and ANN in the assignment of fish to their regions of sampling using parasite community data. The comparative analyses and the validation experiment with a 'blind' sample confirmed that RF models performed more effectively with a large and diverse training set and a large number of variables. The discrimination results obtained for a migratory fish species with largely overlapping parasite communities reflects the high potential of RF for developing predictive models using data that are both complex and noisy, and indicates that it is a promising tool for parasite tag studies. Our results suggest that parasite community data can be used successfully to discriminate individual cod from the five different regions of the North East Atlantic studied using RF.     

Chlorophyll determination in intact tissues using n,n-dimethylformamide

Photosynthetic pigments from etiolated cucumber (Cucumis sativus var. Beit Alpha improved, Hazera Co., Gedera) cotyledons were extracted by direct immersion of the intact cotyledons into the solvent N,N-dimethylformamide (DMF). The solvent is especially efficient when pigment concentration is low; time and tools are saved and the loss of pigment that usually occurs in more complicated extraction procedures is prevented. The specific absorption coefficient of chlorophyll a in DMF was also determined.     

Large-scale phosphosite quantification in tissues by a spike-in SILAC method

Despite progress in mass spectrometry (MS)-based phosphoproteomics, large-scale in vivo analyses remain challenging. Here we report a 'spike-in' stable-isotope labeling with amino acids in cell culture (SILAC) methodology using standards derived from labeled mouse liver cell lines, using which we analyzed insulin signaling. With this approach we identified 15,000 phosphosites and quantitatively compared 10,000 sites in response to insulin treatment, creating a very large, accurately quantified in vivo phosphoproteome dataset.     

Large-scale global identification of protein lysine methylation in vivo

Lysine methylation mediated by methyltransferase enzymes is present on multiple proteins throughout the cell; however, methods to uncover and characterize global protein lysine methylation patterns do not readily exist. Here we developed pan-specific methyl lysine antibodies that we utilized in immunoprecipitation experiments coupled with mass spectrometry to yield one of the first large-scale surveys of protein lysine methylation in vivo. In total, 552 different lysine methylation sites were determined, making this one of the most comprehensive global studies published to date. The large majority of these sites have not been yet reported. These sites showed significantly enriched sequence motifs and resided in proteins that are involved in diverse biological processes, particularly in chromatin organization. Our data provide a comprehensive view of lysine methylation in human cells and a powerful resource to facilitate investigations into the function of lysine methylation on non-histone proteins.     

CpG island methylation pattern in different human tissues and its correlation with gene expression

The study on DNA methylation pattern in different human tissues attracts increasing interest nowadays, but a systematic analysis of CpG island methylation pattern between both somatic tissues and gametocyte is still lacking. In this work, we analyzed the CpG island methylation data of sperm and other 11 somatic tissues from Human Epigenome Project, and found that the CpG island methylation profiles are highly correlated between somatic tissues, while the methylation profile in sperm is quite distinct. Furthermore, we observed that in the six tissues investigated, there is no obvious correlation between the methylation level of promoter CpG islands and corresponding gene expression across different tissues.     

Applying a targeted label-free approach using LC-MS AMT tags to evaluate changes in protein phosphorylation following phosphatase inhibition

To identify phosphoproteins regulated by the phosphoprotein phosphatase (PPP) family of S/T phosphatases, we performed a large-scale characterization of changes in protein phosphorylation on extracts from HeLa cells treated with or without calyculin A, a potent PPP enzyme inhibitor. A label-free comparative phosphoproteomics approach using immobilized metal ion affinity chromatography and targeted tandem mass spectrometry was employed to discover and identify signatures based upon distinctive changes in abundance. Overall, 232 proteins were identified as either direct or indirect targets for PPP enzyme regulation. Most of the present identifications represent novel PPP enzyme targets at the level of both phosphorylation site and protein. These include phosphorylation sites within signaling proteins such as p120 Catenin, A Kinase Anchoring Protein 8, JunB, and Type II Phosphatidyl Inositol 4 Kinase. These data can be used to define underlying signaling pathways and events regulated by the PPP family of S/T phosphatases.     

Identification of intrahepatic cholangiocarcinoma related genes by comparison with normal liver tissues using expressed sequence tags

Intrahepatic cholangiocarcinoma (ICC), a malignant tumor derived from the bile duct epithelium, is one of the leading causes of death from cancer, worldwide. However, the mechanisms related to it remain largely unknown. In this study, an analysis of the gene expression profiles for ICC was done using the frequency of the ESTs obtained from nine cDNA libraries that constructed from 4 ICC cell lines and 4 normal liver tissues. One hundred and thirty-seven genes were identified as being either up- or down-regulated in human ICC cells. Thirty genes were randomly selected to confirm their differential expression in 4 human ICC cell lines and 5 ICC tissues compared to normal liver tissues by semi-quantitative RT-PCR. Among these genes, ANXA1, ANXA2, AMBP, and SERPINC1 were further verified by immunohistochemical analyses. In conclusion, these identified genes represent potential biomarkers for ICC and represent potential targets for elucidating the molecular mechanisms that are associated with ICC.