Project description:Genome editing was conducted on a t(3;8) K562 model to investigate the effects of deleting different modules or CTCF binding sites within the MYC super-enhancer. To check mutations after targeting with CRISPR-Cas9 we performed amplicon sequencing using the Illumina PCR-based custom amplicon sequencing method using the TruSeq Custom Amplicon index kit (Illumina). The first PCR was performed using Q5 polymerase (NEB), the second nested PCR with KAPA HiFi HotStart Ready mix (Roche). Samples were sequenced paired-end (2x 250bp) on a MiSeq (Illumina).
Project description:Long read SMRT cDNA sequencing of nascent RNA from exponentially growing S. cerevisiae and S. pombe cells was employed to obtain transcription elongation and splicing information from single transcripts. Nascent RNA was prepared from the yeast chromatin fraction (Carrillo Oesterreich, Preibisch, Neugebauer, Mol Cell 2010). The nascent 3â?? end was labeled with a 3â?? DNA adaptor through ligation. The adaptor sequence served as template for full-length reverse transcription and double-stranded cDNA was obtained in a PCR (gene-specific or transcriptome-wide). SMRT DNA sequencing libraries were prepared subsequently. Nascent RNA profiles for mainly intron-containing genes were generated with long-read SMRT cDNA sequencing.
Project description:In developing B cells the immunoglobulin heavy chain (IgH) locus is thought to move from repressive to permissive chromatin compartments to facilitate its scheduled rearrangement. In mature B cells, maintenance of allelic exclusion has been proposed to involve recruitment of the non-productive IgH allele to pericentromeric heterochromatin. Here we used an allele-specific chromosome conformation capture combined with sequencing (4C-seq) approach to unambigously follow the individual IgH alleles in mature B lymphocytes. Despite their physical and functional difference, productive and non-productive IgH alleles in B cells and unrearranged IgH alleles in T cells share many chromosomal contacts and largely reside in active chromatin. In brain, however, the locus resides in a different, repressive environment. We conclude that IgH adopts a lymphoid-specific nuclear location that is however unrelated to maintenance of allelic exclusion. We additionally find that in mature B cells - but not in T cells – the distal VH regions of both IgH alleles position themselves away from active chromatin. This, we speculate, may help to restrict enhancer activity to the productively rearranged VH promoter element.
Project description:In developing B cells the immunoglobulin heavy chain (IgH) locus is thought to move from repressive to permissive chromatin compartments to facilitate its scheduled rearrangement. In mature B cells, maintenance of allelic exclusion has been proposed to involve recruitment of the non-productive IgH allele to pericentromeric heterochromatin. Here we used an allele-specific chromosome conformation capture combined with sequencing (4C-seq) approach to unambigously follow the individual IgH alleles in mature B lymphocytes. Despite their physical and functional difference, productive and non-productive IgH alleles in B cells and unrearranged IgH alleles in T cells share many chromosomal contacts and largely reside in active chromatin. In brain, however, the locus resides in a different, repressive environment. We conclude that IgH adopts a lymphoid-specific nuclear location that is however unrelated to maintenance of allelic exclusion. We additionally find that in mature B cells - but not in T cells – the distal VH regions of both IgH alleles position themselves away from active chromatin. This, we speculate, may help to restrict enhancer activity to the productively rearranged VH promoter element. Allele specific analysis of the nuclear organization of the IgH locus in resting and activated B cells and T cells and fetal brain cells
Project description:Amplicon-based targeted re-sequencing analysis was performed in the patient-derived gliobastoma cell culture samples. For this purpose, genomic DNA (gDNA) was isolated and DNA libraries were prepared using the TruSeq Custom Amplicon Low Input (Illumina, Inc.) technology. By this, a pool of 375 amplicons was generated for each single sample in order to enrich for the target genes ATRX1, EGFR, IDH1, NF1, PDGFRA, PIK3CG, PIK3R1, PTEN, RB1 and TP53. Sequencing was performed on the Illumina MiSeq® next generation sequencing system (Illumina Inc.) and its 2 x 250 bp paired-end v2 read chemistry. The resulting reads were quality controlled and mapped against the human reference genome (hg19). For all samples, sequence variations of the amplified regions of interest in comparison to the human reference sequence were identified and filtered based on reliability.
Project description:Standardisation of Immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages commonly used to interrogate immunopeptidomics datasets, in order to understand to which extent differences in performance can be observed. We found that a de novo-assisted database search reports substantially more peptide sequences (~30-70%) compared to three database search engines at a global FDR of <1%. This effect was reproducible across four immunopeptidomic datasets. We validated the results using data generated with a synthetic library of 2000 HLA-associated peptides from four HLA alleles, half of which were previously observed by LC-MS, and half were predicted only. Our investigation reveals that search engines create a bias in peptide sequence length distribution and peptide amino acid composition. Therefore, the choice of peptide identification method highly influences the proportion of peptide sequences identified for each HLA allele, and resulting data should be interpreted with caution.
Project description:In recent years, long-read sequencing technologies have detected transcript isoforms with unprecedented accuracy and resolution. However, it remains unclear whether long-read sequencing can effectively disentangle the isoform landscape of complex allele-specific loci that arise from genetic or epigenetic differences between alleles. Here, we combine the PacBio Iso-Seq workflow with the established phasing approach WhatsHap to assign long reads to the corresponding allele in polymorphic F1 mouse hybrids. Upon comparing the long-read sequencing results with matched short reads, we observed general consistency in the allele-specific information and were able to confirm the imprinting status of known imprinted genes. We then explored the complex imprinted Gnas locus known for allele-specific non-coding and coding isoforms and were able to benchmark historical observations. This approach also allowed us to detect isoforms from both the active and inactive X chromosomes of genes that escape X chromosome inactivation. The described workflow offers a promising framework and demonstrates the power of long-read transcriptomic data to provide mechanistic insight into complex allele-specific loci.
2025-02-03 | GSE246857 | GEO
Project description:Amplicon sequencing of edited OpenCell alleles
Project description:Long-read SMRT cDNA sequencing of nascent RNA from exponentially growing S. pombe cells was employed to obtain transcription elongation and splicing information from single transcripts. Nascent RNA was prepared from the yeast chromatin fraction (Carrillo Oesterreich, Preibisch, Neugebauer, Mol Cell 2010). The nascent 3’ end was labeled with a 3’ DNA adaptor through ligation. The adaptor sequence served as template for full-length reverse transcription and double-stranded cDNA was obtained in a transcriptome-wide PCR. SMRT DNA sequencing libraries were prepared subsequently.
Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications