Morlighem J.-E.,RIKEN |
Harbers M.,RIKEN |
Harbers M.,DNAFORM Inc. |
Traeger-Synodinos J.,National and Kapodistrian University of Athens |
Pharmacogenomics | Year: 2011
The variable predisposition of patients, both to disease susceptibility and drug response, is well established. It is largely attributed to genetic, as well as epigenetic variations between individuals, which may be inherited or acquired. The most common variation in the human genome is the SNP, which occurs throughout the genome, both within coding and noncoding regions. Characterization of SNPs in the context of both inherited and acquired conditions, such as cancer, are a main focus of many genotyping procedures. The demand for identifying (diagnosing) targeted SNPs or other variations, as well as the application of genome-wide screens, is continuously directing the development of new technologies. In general, most methods require a DNA amplification step to provide the amounts of DNA needed for the SNP detection step. In addition, DNA amplification is an important step when investigating other types of genomic information, for instance when addressing repeat, deletion, copy number variation or epigenetic regulation by DNA methylation. Besides the widely used PCR technique, there are several alternative approaches for genomic DNA amplification suitable for supporting the detection of genomic variation. In this article, we describe and evaluate a number of techniques, and discuss possible future prospects of DNA amplification in the fields of pharmacogenetics and pharmacogenomics. © 2011 Future Medicine Ltd.
Cheng C.,National Institute of Genetics |
Cheng C.,Japan National Institute of Agrobiological Science |
Cheng C.,DNAFORM Inc. |
Tarutani Y.,National Institute of Genetics |
And 6 more authors.
Plant Journal | Year: 2015
Methylation patterns of plants are unique as, in addition to the methylation at CG dinucleotides that occurs in mammals, methylation also occurs at non-CG sites. Genes are methylated at CG sites, but transposable elements (TEs) are methylated at both CG and non-CG sites. The role of non-CG methylation in transcriptional silencing of TEs is being extensively studied at this time, but only very rare transpositions have been reported when non-CG methylation machineries have been compromised. To understand the role of non-CG methylation in TE suppression and in plant development, we characterized rice mutants with changes in the chromomethylase gene, OsCMT3a. oscmt3a mutants exhibited a dramatic decrease in CHG methylation, changes in the expression of some genes and TEs, and pleiotropic developmental abnormalities. Genome resequencing identified eight TE families mobilized in oscmt3a during normal propagation. These TEs included tissue culture-activated copia retrotransposons Tos17 and Tos19 (Lullaby), a pericentromeric clustered high-copy-number non-autonomous gypsy retrotransposon Dasheng, two copia retrotransposons Osr4 and Osr13, a hAT-tip100 transposon DaiZ, a MITE transposon mPing, and a LINE element LINE1-6-OS. We confirmed the transposition of these TEs by polymerase chain reaction (PCR) and/or Southern blot analysis, and showed that transposition was dependent on the oscmt3a mutation. These results demonstrated that OsCMT3a-mediated non-CG DNA methylation plays a critical role in development and in the suppression of a wide spectrum of TEs. These in planta mobile TEs are important for studying the interaction between TEs and the host genome, and for rice functional genomics. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.
Hestand M.S.,Leiden University |
Klingenhoff A.,Genomatix Software GmbH |
Scherf M.,Genomatix Software GmbH |
Ariyurek Y.,Leiden University |
And 8 more authors.
Nucleic Acids Research | Year: 2010
Next-generation sequencing is excellently suited to evaluate the abundance of mRNAs to study gene expression. Here we compare two alternative technologies, cap analysis of gene expression (CAGE) and serial analysis of gene expression (SAGE), for the same RNA samples. Along with quantifying gene expression levels, CAGE can be used to identify tissue-specific transcription start sites, while SAGE monitors 3′-end usage. We used both methods to get more insight into the transcriptional control of myogenesis, studying differential gene expression in differentiated and proliferating C2C12 myoblast cells with statistical evaluation of reproducibility and differential gene expression. Both CAGE and SAGE provided highly reproducible data (Pearson's correlations >0.92 among biological triplicates). With both methods we found around 10 000 genes expressed at levels >2 transcripts per million (~0.3 copies per cell), with an overlap of 86%. We identified 4304 and 3846 genes differentially expressed between proliferating and differentiated C2C12 cells by CAGE and SAGE, respectively, with an overlap of 2144. We identified 196 novel regulatory regions with preferential use in proliferating or differentiated cells. Next-generation sequencing of CAGE and SAGE libraries provides consistent expression levels and can enrich current genome annotations with tissue-specific promoters and alternative 3′-UTR usage. © The Author(s) 2010. Published by Oxford University Press.