3855 results for "*geneti*"

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• Walter and Eliza Hall - Aix-Marseille Université

  Data Access Committee for the Liao et al. 2025 study, D4Z4End2End: complete genetic and epigenetic architecture of D4Z4 macrosatellites in FSHD, BAMS and reference cohorts.

  Dac EGAC50000000655

• genetic analysis of carcinogenesis in GAPPS

  Gastric adenocarcinoma and proximal polyposis of the stomach (GAPPS) is an autosomal dominant syndrome characterized by polyposis localized in the gastric body and fundus with a strong tendency for adenocarcinoma. The genetic mutations that accumulate during the progression from normal mucosa through fundic gland polyps (FGPs) to carcinoma in GAPPS remain unclear.We investigated the evolutionary process from normal mucosa to FGPs and carcinoma in GAPPS. Through comprehensive mutational and transcriptome analyses, we aimed to provide insights into the biology of this disease.

  Study JGAS000843

• The Genetic Analysis of multiple sclerosis

  We created these data in order to identify genetic variants associated with increased susceptibility to multiple sclerosis. Cases from many parts of the world were genotyped with the Illumina 660 chip along with Swedish controls. In our analysis we also used control data from the WTCCC2 common UK controls and from other published studies.

  Study EGAS00000000101

• The brain neurovascular epigenome and its association with dementia

  Cerebral small vessel disease (SVD) is frequently comorbid with Alzheimer’s disease (AD) and vascular brain endothelial cells (BECs) are enriched for the expression of genes associated with AD genetic risk. However, the gene regulatory landscapes of neurovascular cells and their intersection with genetic risk for disease remains unexplored. Here we have generated gene regulomes for human BECs, mural cells and other brain cell types to show that AD heritability is primarily immune-related and that it shows modest enrichment in BECs. By contrast, genetic risk for SVD is enriched across cells of the neurovascular unit, including astrocytes. Enhancer-to-gene interactomes implicate amyloid processes in both AD and SVD, though the risk genes are mostly distinct for the two disorders. Motifs for putative partners of lineage transcription factors in microglia and BECs were enriched for AD and SVD variants at genes linked to disease pathways. Gene prioritization and enrichment analyses further identified potential repurposable drugs for AD. Our findings highlight novel regulatory mechanisms and therapeutic targets within the neurovascular system.

  Study EGAS50000001160

• Huch Lab, Max Planck Institute of Molecular Cell Biology and Genetics

  Dac EGAC50000000112

• APC-related multiple salivary gland lesions

  This study aims to investigate the genetic and molecular mechanisms underlying a novel phenotype of attenuated familial adenomatous polyposis (AFAP), where affected individuals develop multiple salivary gland tumours, including basal cell adenomas and adenocarcinomas.

  Study EGAS50000001159

• Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

  DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

  Study EGAS50000000541

• LifeChange Data Access Committee

  The LifeChange study aimed at tracking the biological consequences of the societal changes undergone by the Yakut people of Far Eastern Siberia, after the colonization of the region by Russians in the 17th century. This study builds upon more than 15 years of archaeological research conducted in Yakutia, Sakha Republic, an autonomous region of the Russian Federation located in northeastern Siberia. The fieldwork was conducted under the MAFSO program (“Mission Archéologique Française en Sibérie Orientale”, or “French Archaeological Mission in Eastern Siberia”), a collaboration between French researchers and local Yakut experts, including scholars from North-Eastern Federal University in Yakutsk. The program was supported by several inter-university collaborative research agreements, notably between Université Paul Sabatier, Krasnoyarsk State Medical University, and North-Eastern Federal University in Yakutsk. It also received endorsement from the Institute of Ecology and Evolution at CNRS through the International Associated Laboratory “Co-evolution Human-Environment in Eastern Siberia”. The LifeChange Data Access Committee, composed of French and Russian archaeogeneticists, geneticists and archaeologists, reviews any access request to LifeChange data, consisting of genomes of ancient and modern Yakut, Eveni and Evenki individuals sampled in Eastern Siberia for the LifeChange study. The DAC grants access to any academic researcher aiming to study the population history of autochthonous peoples from Siberia. When reviewing data access requests, the DAC members ensure that the applicant will not re-use the data to trace present-day descendants of studied ancient individuals. They also ensure that secondary use of the modern genomic data is conducted in full respect of the conditions stipulated in living participants’ informed consent. Specifically, the applicant is not authorised to (i) use the data for diagnostic purposes, (ii) store the data outside of secure servers, (iii) reidentify research participants, and (iv) share the data with a third party.

  Dac EGAC50000000713

• Recurrent intra-tumour heterogeneity is a hallmark of metastatic prostate cancer

  The evolution of cancers from low grade to metastatic disease is a major determinant of cancer mortality. Cancer evolution involves a complex interplay between cell intrinsic genetics and transcriptional alterations and the extrinsic microenvironment. To define the key mechanisms underpinning metastatic development, we focused on the most lethal form of prostate cancer, metastatic castration-resistant prostate cancer, and employed single-cell multi-omics and whole-genome sequencing to deeply profile 34 metastatic lesions from 9 patients obtained from rapid autopsy. We found that intra-tumour heterogeneity is an indicator of key evolutionary processes, characterised by recurrent tumour populations acting as critical functional components of the tumour ecosystem, irrespective of clonal and microenvironmental backgrounds. Unexpectedly, microenvironments across metastatic sites played a limited role while clonal evolution primarily promoted transcriptional noise. Intra-patient functional convergence of tumour ecosystems was observed across metastatic sites, pointing towards system-level selection pressures that drive the heterogeneity landscape of mCRPC. Our findings reveal functional evolutionary convergence of metastatic disease into units of intra-tumour heterogeneity identifying critical determinants of metastatic progression for therapeutic targeting. Note: matched WGS for some tumour single-cell experiments, as well as germline WGS for patients CA0027, CA0034, CA0035, CA0043, and CA0076, can be found in EGAS00001006598.

  Study EGAS50000001312

• UMCG Immunogenetics DAC

  DAC for the data generated in the Immunogenetics group in the genetics department of the University Medical Center Groningen

  Dac EGAC50000000785