4051 results for "*geneti*"

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• Genotype data for The admixture histories of Cabo Verde - genotype data

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) As per Materials and Methods herein, the genotype data corresponds to 2,118,722 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 233 Cabo Verdean volunteer participants, family unrelated at the 2nd degree based on population genetics analyses (see Material and Methods). SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38. Cabo Verdean individuals are designated with an alphanumeric unique code

  Dataset EGAD00001008979

• Anthropological dataset 1 for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_233CaboVerde_SampleInfo_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file Column 2 corresponds to individual's biological sex as per genetic inference Column 3 corresponds to individual's self-reported age in years Column 4 corresponds to individual's self-reported cumulated number of years spent in academic or professional education

  Dataset EGAD00001008976

• Anthropological dataset 2 for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_233CaboVerde_GEOcoordFULL_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file Column 2-3 corresponds to X-Y GPS coordinates of individual's interview location in Cabo Verde Column 4-5 corresponds to X-Y GPS coordinates of individual's self-reported residence location at the time of the interview Column 6-7 corresponds to X-Y GPS coordinates of individual's self-reported birth-place location Column 8-9 corresponds to X-Y GPS coordinates of individual's self-reported paternal birth-place location Column 10-11 corresponds to X-Y GPS coordinates of individual's self-reported maternal birth-place location

  Dataset EGAD00001008977

• Linguistic utterance counts for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

  Dataset EGAD00001008978

• Exome Sequencing of 44 subjects with very severe or fatal COVID-19

  In this study, the DNA of 44 subjects with severe COVID-19 have been sequenced in order to explore rare genetic variants.

  Dataset EGAD00001008993

• HSP90 inhibitor resistant K562 cells

  K562 cell line has been treated with two different HSP90 inhibtors. After resistance clones emerged, they have been genetically characterized using WES in comparison to the parental K562 cell line.

  Dataset EGAD00001009051

• Single-cell study of 14 childhood medulloblastoma patients

  Medulloblastoma intra-tumoural genetic heterogeneity and clonal evolution, and their role in disease pathogenesis and clinical behaviour, are poorly understood. We used single-cell whole-genome sequencing (sc-WGS) to reconstruct the natural history and temporal evolution of 14 medulloblastomas, representing its major clinico-molecular sub-classes. We identified wholly-clonal tumours which displayed single-clone expansion (i.e. linear evolution); all were observed in favourable-outcome sub-classes (i.e. MBWNT and infant MBSHH). In contrast, remaining tumours harboured sub-clonal structures which displayed punctuated or gradual trajectories; highest-risk sub-classes, typically characterised by MYC-amplification (MBGroup3) or TP53-mutation (MBSHH), and linked to genomic instability and LCA pathology, were most clonally-diverse. Clinically-adopted biomarkers were typically early-clonal/initiating events, representing exploitable targets for early-disease detection; in analyses of spatially-distinct tumour regions, a single biopsy was sufficient to assess their status. sc-WGS revealed events not previously appreciated in bulk tumour analysis, which arose later and/or sub-clonally and more commonly displayed spatial diversity; their clinical significance and role in disease evolution post-diagnosis now require establishment. In summary, our findings reveal diverse modes of tumour initiation and clonal evolution in the major medulloblastoma sub-classes, highlighting their pathogenic relevance and clinical potential.

  Dataset EGAD00001009057

• Convergent somatic evolution from early life in a germline ribosomopathy

  Clonal tracking of stem cells and their progeny by whole genome sequencing permits exploration of evolutionary genetics in human disease. In this study, we performed phylogenetic reconstruction of haematopoiesis using somatically acquired mutations in 323 single haematopoietic stem and progenitor cell-derived colonies from 10 individuals with an inherited disorder of ribosome assembly, Shwachman-Diamond syndrome. We observed numerous clonal expansions, with recurrent acquisition of mutually exclusive mutations (EIF6, TP53, RPL5, RPL22, PRPF8, chromosomes 7 and 15) in multiple different clones in utero or early childhood converging on the p53-dependent nucleolar surveillance pathway that monitors ribosome integrity. In contrast to clones carrying biallelic TP53 mutations, genomes derived from colonies carrying mono-allelic TP53 mutations displayed no increase in mutation burden or specific mutational signatures. Our study highlights striking loss of clonal diversity with convergent somatic evolution on the p53-dependent nucleolar surveillance pathway from early life to offset the deleterious effects of a germline mutation in a Mendelian haematopoietic disorder.

  Dataset EGAD00001009061

• Oropharyngeal Squamous Cell Carcinoma Mutanome

  This dataset comprises genetic variation data (as somatic indels and snvs VCFs) of 38 OPSCC tumors. WES was done using NextSeq 500 System running in 150 cycles (2x 75bp paired-end) mode. Sequence information was converted to FASTQ format using bcl2fastq v2.20.0.422. VCFs were generated using the Strelka package.

  Dataset EGAD00001009167

• Clonal origin of lineage switch leukemia following CAR-T cell and blinatumomab therapy

  Children with ALL treated with anti-CD19 therapy occasionally develop a phenotypically distinct AML. However, the precise clonal origin of such class switch leukemias remains unresolved. Here, we reconstructed the evolution of leukemia in a child with primary ALL, two ALL relapses and AML after treatment with anti-CD19 CAR-T and blinatumomab through whole-genome sequencing. The phylogeny revealed that the AML was a monoclonal outgrowth descending from the initial ALL and harbored biallelic loss of CDKN2A, PAX5 and TP53. However, none of the ALL or AML relapses directly descended from one another, suggesting the presence of a reservoir of persistent clones. Our findings suggest anti-CD19 treatment selects pre-existing clones, with many key genetic alterations underpinning the lineage switch detectable prior to treatment.

  Dataset EGAD00001009161