Similar Datasets
Project description:Antitype chi genome assembly, ilAntChix2, alternate haplotype
| PRJEB57612 | ENA
Project description:Spiroplasma endosymbiont of Antitype chi genome assembly, ilAntChix2.Spiroplasma_sp_1
| PRJEB74376 | ENA
Project description:Chronic histiocytic intervillositis of unknown origin (CHI) is a rare placental disorder associated with adverse pregnancy outcomes, frequent recurrence, and a lack of effective preventive strategies. Recent insights indicate a potential link between CHI-associated inflammatory lesions and the inflammasome pathway, suggesting innovative therapeutic avenues. Here we show a potential role of the inflammasome pathway in CHI through comprehensive transcriptomic analysis of grade 2 or 3 histopathologic CHI samples, paired with placental controls. Additionally, we present case studies of three individuals with recurrent CHI, who have undergone treatment with anakinra and colchicine throughout pregnancy, resulting in improved perinatal outcomes. Notably, all cases are characterised by the birth of healthy, full-term infants, with reduced or absent intervillositis recurrence. Placental assessment unveils heightened activation of the NLRP3-PYCARD inflammasome pathway and IL-1β processing in CHI samples, with downregulation observed in treated pregnancy samples, devoid of intervillositis. Collectively, these findings suggest a potential therapeutic role for targeting the inflammasome pathway in preventing recurrent CHI in pregnant individuals
2024-07-29 | GSE272505 | GEO
Project description:Capture Hi-C (CHi-C) is a state-of-the art method for profiling chromosomal interactions involving targeted regions of interest (such as gene promoters) globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model, and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments, in which many spatially dispersed regions are captured, such as in Promoter CHi-C. We implement these procedures in CHiCAGO (http://regulatorygenomicsgroup.org/chicago), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs.
2016-05-18 | GSE81503 | GEO
Project description:Capture Hi-C (CHi-C) is a state-of-the art method for profiling chromosomal interactions involving targeted regions of interest (such as gene promoters) globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model, and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments, in which many spatially dispersed regions are captured, such as in Promoter CHi-C. We implement these procedures in CHiCAGO (http://regulatorygenomicsgroup.org/chicago), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs. Three human CHi-C biological replicates were generated (comprising 1, 2and 3 technical replicates). Two mouse CHi-C biological replicates were generated (both comprising three technical replicates) and a mouse Hi-C dataset. The publicly available HiCUP pipeline (doi: 10.12688/f1000research.7334.1) was used to process the raw sequencing reads. This pipeline was used to map the read pairs against the mouse (mm9) and human (hg19) genomes, to filter experimental artefacts (such as circularized reads and re-ligations), and to remove duplicate reads. For the CHi-C data, the resulting BAM files were processed into CHiCAGO input files, retaining only those read pairs that mapped, at least on one end, to a captured bait. CHiCAGO then identified Hi-C restriction fragments interacting, with statistical significant, to captured baits.
2016-05-18 | E-GEOD-81503 | biostudies-arrayexpress
Project description:Genome organization influences transcriptional regulation by facilitating interactions between gene promoters and distal regulatory elements. To analyse distal promoter contacts we used Capture Hi-C (CHi-C) to enrich for promoter-interactions in a HiC lib
2015-03-01 | E-MTAB-2323 | biostudies-arrayexpress