5-hmC in the brain: abundance in synaptic genes and differences at the exon-intron boundary
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE40167 | GEO | 2012/08/24
SECONDARY ACCESSION(S): PRJNA173636
REPOSITORIES: GEO
Similar Datasets
Project description:5-hydroxymethylcytosine (5-hmC), a derivative of 5-methylcytosine (5-mC), is abundant in the brain for unknown reasons. We mapped the genomic distribution of 5-hmC and 5-mC in human and mouse tissues using glucosylation of 5-hmC coupled with restriction enzyme digestion, and interrogation on microarrays. We detected 5-hmC enrichment in genes with synapse-related functions in the brain. We also identified significant, tissue-specific differential distributions of these DNA modifications at the exon-intron boundary, in both human and mouse. This boundary change was mainly due to 5-hmC in the brain, but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent datasets, and the brain-specific change in 5-hmC was validated using single-molecule sequencing. Moreover, in the brain, constitutive exons contained higher levels of 5-hmC, relative to alternatively-spliced exons. Our study suggests a novel role for 5-hmC in RNA splicing and synaptic function in the brain
2012-08-24 | GSE40166 | GEO
Project description:5-hydroxymethylcytosine (5-hmC), a derivative of 5-methylcytosine (5-mC), is abundant in the brain for unknown reasons. We mapped the genomic distribution of 5-hmC and 5-mC in human and mouse tissues using glucosylation of 5-hmC coupled with restriction enzyme digestion, and interrogation on microarrays. We detected 5-hmC enrichment in genes with synapse-related functions in the brain. We also identified significant, tissue-specific differential distributions of these DNA modifications at the exon-intron boundary, in both human and mouse. This boundary change was mainly due to 5-hmC in the brain, but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent datasets, and the brain-specific change in 5-hmC was validated using single-molecule sequencing. Moreover, in the brain, constitutive exons contained higher levels of 5-hmC, relative to alternatively-spliced exons. Our study suggests a novel role for 5-hmC in RNA splicing and synaptic function in the brain
2012-08-24 | GSE40158 | GEO
Project description:5-hydroxymethylcytosine (5-hmC), a derivative of 5-methylcytosine (5-mC), is abundant in the brain for unknown reasons. We mapped the genomic distribution of 5-hmC and 5-mC in human and mouse tissues using glucosylation of 5-hmC coupled with restriction enzyme digestion, and interrogation on microarrays. We detected 5-hmC enrichment in genes with synapse-related functions in the brain. We also identified significant, tissue-specific differential distributions of these DNA modifications at the exon-intron boundary, in both human and mouse. This boundary change was mainly due to 5-hmC in the brain, but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent datasets, and the brain-specific change in 5-hmC was validated using single-molecule sequencing. Moreover, in the brain, constitutive exons contained higher levels of 5-hmC, relative to alternatively-spliced exons. Our study suggests a novel role for 5-hmC in RNA splicing and synaptic function in the brain The M-NM-2-glucosyltransferase (BGT) enzyme transfers a glucose molecule specifically to the hydroxymethyl group of 5-hmC, thus rendering it resistant to digestion by the methylation insensitive MspI enzyme at the ChmCGG target site; 5-hmC is thus detected by differential resistance to MspI-digestion with and without glucosylation of genomic DNA (gDNA). HpaII (targets the same site, CCGG) cannot cut CmCGG or ChmCGG, and conceptually its difference with MspI digestion is a measure of both 5-mC and 5-hmC. Subtraction of 5-hmC from the HpaII-based estimate therefore measures 5-mC. These estimates were measured on respective Affymetrix whole-genome tiling arrays (2.0 R ) MspI - APRIL_fc1.ch02_coverage.bed Undigested DNA - APRIL_fc1.ch01_coverage.bed GluMspI - APRIL_fc1.ch04_coverage_NONTARGET.bed GluMspI - APRIL_fc1.ch04_coverage.bed MspI - APRIL_fc1.ch02_coverage_NONTARGET.bed Undigested DNA - APRIL_fc1.ch01_coverage_NONTARGET.bed MspI - MARCH_fc1.ch02_coverage_NONTARGET.bed Undigested DNA - MARCH_fc1.ch01_coverage_NONTARGET.bed GluMspI - MARCH_fc1.ch04_coverage_NONTARGET.bed GluMspI - MARCH_fc1.ch04_coverage.bed MspI - MARCH_fc1.ch02_coverage.bed Undigested DNA - MARCH_fc1.ch01_coverage.bed MspI - MAY_fc1.ch02_coverage.bed GluMspI - MAY_fc1.ch04_coverage_NONTARGET.bed GluMspI - MAY_fc1.ch04_coverage.bed Undigested DNA - MAY_fc1.ch01_coverage.bed MspI - MAY_fc1.ch02_coverage_NONTARGET.bed Undigested DNA - MAY_fc1.ch01_coverage_NONTARGET.bed
2012-08-24 | E-GEOD-40158 | biostudies-arrayexpress
Project description:The 5-methylcytosine (5-mC) derivative 5-hydroxymethylcytosine (5-hmC) is abundant in the brain for unknown reasons. Here we characterize the genomic distribution of 5-hmC and 5-mC in human and mouse tissues. We assayed 5-hmC by using glucosylation coupled with restriction-enzyme digestion and microarray analysis. We detected 5-hmC enrichment in genes with synapse-related functions in both human and mouse brain. We also identified substantial tissue-specific differential distributions of these DNA modifications at the exon-intron boundary in human and mouse. This boundary change was mainly due to 5-hmC in the brain but due to 5-mC in non-neural contexts. This pattern was replicated in multiple independent data sets and with single-molecule sequencing. Moreover, in human frontal cortex, constitutive exons contained higher levels of 5-hmC relative to alternatively spliced exons. Our study suggests a new role for 5-hmC in RNA splicing and synaptic function in the brain.
| S-EPMC3465469 | biostudies-literature
Project description:5-hmC in the brain: abundance in synaptic genes and differences at the exon-intron boundary
| PRJNA173636 | ENA
Project description:5-hmC in the brain: abundance in synaptic genes and differences at the exon-intron boundary (tiling array)
| PRJNA173642 | ENA
Project description:BACKGROUND:In-depth study of the intron retention levels of transcripts provide insights on the mechanisms regulating pre-mRNA splicing efficiency. Additionally, detailed analysis of retained introns can link these introns to post-transcriptional regulation or identify aberrant splicing events in human diseases. RESULTS:We present IntEREst, Intron-Exon Retention Estimator, an R package that supports rigorous analysis of non-annotated intron retention events (in addition to the ones annotated by RefSeq or similar databases), and support intra-sample in addition to inter-sample comparisons. It accepts binary sequence alignment/map (.bam) files as input and determines genome-wide estimates of intron retention or exon-exon junction levels. Moreover, it includes functions for comparing subsets of user-defined introns (e.g. U12-type vs U2-type) and its plotting functions allow visualization of the distribution of the retention levels of the introns. Statistical methods are adapted from the DESeq2, edgeR and DEXSeq R packages to extract the significantly more or less retained introns. Analyses can be performed either sequentially (on single core) or in parallel (on multiple cores). We used IntEREst to investigate the U12- and U2-type intron retention in human and plant RNAseq dataset with defects in the U12-dependent spliceosome due to mutations in the ZRSR2 component of this spliceosome. Additionally, we compared the retained introns discovered by IntEREst with that of other methods and studies. CONCLUSION:IntEREst is an R package for Intron retention and exon-exon junction levels analysis of RNA-seq data. Both the human and plant analyses show that the U12-type introns are retained at higher level compared to the U2-type introns already in the control samples, but the retention is exacerbated in patient or plant samples carrying a mutated ZRSR2 gene. Intron retention events caused by ZRSR2 mutation that we discovered using IntEREst (DESeq2 based function) show considerable overlap with the retained introns discovered by other methods (e.g. IRFinder and edgeR based function of IntEREst). Our results indicate that increase in both the number of biological replicates and the depth of sequencing library promote the discovery of retained introns, but the effect of library size gradually decreases with more than 35 million reads mapped to the introns.
| S-EPMC5896110 | biostudies-literature
Project description:The Exon/Intron (ExInt) database incorporates information on the exon/intron structure of eukaryotic genes. Features in the database include: intron nucleotide sequence, amino acid sequence of the corresponding protein, position of the introns at the amino acid level and intron phase. From ExInt, we have also generated four additional databases each with ExInt entries containing predicted introns, introns experimentally defined, organelle introns or nuclear introns. ExInt is accessible through a retrieval system with pointers to GenBank. The database can be searched by keywords, locus name, NID, accession number or length of the protein. ExInt is freely accessible at http://intron.bic.nus.edu.sg/exint/exint.html
| S-EPMC102468 | biostudies-literature
Project description:Gene duplication plays key roles in organismal evolution. Duplicate genes, if they survive, tend to diverge in regulatory and coding regions. Divergences in coding regions, especially those that can change the function of the gene, can be caused by amino acid-altering substitutions and/or alterations in exon-intron structure. Much has been learned about the mode, tempo, and consequences of nucleotide substitutions, yet relatively little is known about structural divergences. In this study, by analyzing 612 pairs of sibling paralogs from seven representative gene families and 300 pairs of one-to-one orthologs from different species, we investigated the occurrence and relative importance of structural divergences during the evolution of duplicate and nonduplicate genes. We found that structural divergences have been very prevalent in duplicate genes and, in many cases, have led to the generation of functionally distinct paralogs. Comparisons of the genomic sequences of these genes further indicated that the differences in exon-intron structure were actually accomplished by three main types of mechanisms (exon/intron gain/loss, exonization/pseudoexonization, and insertion/deletion), each of which contributed differently to structural divergence. Like nucleotide substitutions, insertion/deletion and exonization/pseudoexonization occurred more or less randomly, with the number of observable mutational events per gene pair being largely proportional to evolutionary time. Notably, however, compared with paralogs with similar evolutionary times, orthologs have accumulated significantly fewer structural changes, whereas the amounts of amino acid replacements accumulated did not show clear differences. This finding suggests that structural divergences have played a more important role during the evolution of duplicate than nonduplicate genes.
| S-EPMC3268293 | biostudies-literature
Project description:Despite significant advances in high-throughput DNA sequencing, many important species remain understudied at the genome level. In this study we addressed a question of what can be predicted about the genome-wide characteristics of less studied species, based on the genomic data from completely sequenced species. Using NCBI databases we performed a comparative genome-wide analysis of such characteristics as alternative splicing, number of genes, gene products and exons in 36 completely sequenced model species. We created statistical regression models to fit these data and applied them to loblolly pine (Pinus taeda L.), an example of an important species whose genome has not been completely sequenced yet. Using these models, the genome-wide characteristics, such as total number of genes and exons, can be roughly predicted based on parameters estimated from available limited genomic data, e.g. exon length and exon/gene ratio.
| S-EPMC3064661 | biostudies-literature