Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA259794 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Concurrent whole-genome haplotyping and copy number profiling of single cells (Illumina)
| PRJNA259796 | ENA
Project description:Single-cell whole-genome haplotyping allows simultaneous detection of haplotypes associated with monogenic diseases, chromosome copy-numbering and subsequently, has revealed mosaicism in embryos and embryonic stem cells. Methods, such as karyomapping and haplarithmisis, were deployed as a generic and genome-wide approach for preimplantation genetic testing (PGT) and are replacing traditional PGT methods. While current methods primarily rely on SNP array, we envision sequencing-based methods to become more accessible and cost-efficient. Here, we developed a novel sequencing-based methodology to haplotype and copy-number profile single cells. Following DNA amplification, genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing. This single-cell genotyping-by-sequencing (scGBS) is the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping. We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells. We demonstrate its value in human blastomere and trophectoderm samples as application for PGT for monogenic disorders. Furthermore, we demonstrate the method to work in other species through analyzing blastomeres of bovine embryos. Our scGBS method opens up the path for single-cell haplotyping of any species with diploid genomes and could make its way into the clinic as a PGT application.
2021-08-18 | GSE178156 | GEO
Project description:Methods for haplotyping and DNA copy number typing of single cells are paramount for studying genomic heterogeneity and enabling genetic diagnosis. Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required that substantially distorts the frequency and composition of the cell’s alleles. As a consequence, haplotyping methods suffer from error-prone discrete SNP-genotypes (AA, AB, BB), and DNA copy number profiling remains difficult as true DNA copy number aberrations have to be discriminated from WGA-artifacts. Here, we developed a single-cell genome analysis method that reconstructs genome-wide haplotype architectures as well as the copy-number and segregational origin of those haplotypes by deciphering WGA-distorted SNP B-allele fractions, using a process we coin haplarithmisis. We demonstrate clinical precision of the method on single cells biopsied from human embryos to diagnose disease alleles genome wide, we advance and facilitate the detection of numerical and structural chromosomal anomalies in single cells, and can distinguish meiotic from mitotic segregation errors in a single assay.
2015-05-15 | GSE60909 | GEO
Project description:Methods for haplotyping and DNA copy number typing of single cells are paramount for studying genomic heterogeneity and enabling genetic diagnosis. Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required that substantially distorts the frequency and composition of the cell’s alleles. As a consequence, haplotyping methods suffer from error-prone discrete SNP-genotypes (AA, AB, BB), and DNA copy number profiling remains difficult as true DNA copy number aberrations have to be discriminated from WGA-artifacts. Here, we developed a single-cell genome analysis method that reconstructs genome-wide haplotype architectures as well as the copy-number and segregational origin of those haplotypes by deciphering WGA-distorted SNP B-allele fractions, using a process we coin haplarithmisis. We demonstrate clinical precision of the method on single cells biopsied from human embryos to diagnose disease alleles genome wide, we advance and facilitate the detection of numerical and structural chromosomal anomalies in single cells, and can distinguish meiotic from mitotic segregation errors in a single assay.
2015-05-15 | GSE60907 | GEO
Project description:Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing
| PRJEB45461 | ENA
Project description:scGBS is a single-cell sequencing-based methodology to haplotype and copy-number profile single cells. Genomic size and complexity is reduced through restriction enzyme digestion and DNA is genotyped through sequencing of the restriction fragments. scGBS data serves as the input for haplarithmisis, an algorithm we previously developed for SNP array-based single-cell haplotyping. We established technical parameters and developed an analysis pipeline enabling accurate concurrent haplotyping and copy-number profiling of single cells.
| EGAS00001005401 | EGA
Project description:Methods for haplotyping and DNA copy number typing of single cells are paramount for studying genomic heterogeneity and enabling genetic diagnosis. Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required that substantially distorts the frequency and composition of the cell’s alleles. As a consequence, haplotyping methods suffer from error-prone discrete SNP-genotypes (AA, AB, BB), and DNA copy number profiling remains difficult as true DNA copy number aberrations have to be discriminated from WGA-artifacts. Here, we developed a single-cell genome analysis method that reconstructs genome-wide haplotype architectures as well as the copy-number and segregational origin of those haplotypes by deciphering WGA-distorted SNP B-allele fractions, using a process we coin haplarithmisis. We demonstrate clinical precision of the method on single cells biopsied from human embryos to diagnose disease alleles genome wide, we advance and facilitate the detection of numerical and structural chromosomal anomalies in single cells, and can distinguish meiotic from mitotic segregation errors in a single assay. The samples of a reference family were applied for optimisation of single-cell genotyping using Affymetrix SNP-arrays prior to downstream analysis. Specifically, the reference family delivers genomic DNA samples isolated from peripheral blood of two siblings 'S1' and 'S2', the mother and father of these siblings, as well as of the maternal grandmother and grandfather. Of individuals ‘S1’ and ‘S2’, six EBV-transformed lymphoblastoid single cells were isolated of which three were whole-genome amplified using MDA and three using PicoPlex. These WGA-products were hybridized to Affymetrix NspI 250K SNP-arrays following the protocol as recommended by the company. Subsequently, the SNP-probe signals were interpreted by different genotyping algorithms (see data processing). Based on overall performance, it was decided to use the Dynamic Model (DM) for interpreting Affymetrix SNP-probe signals of single cells.
2015-05-15 | E-GEOD-60907 | biostudies-arrayexpress
Project description:Single-cell genome-wide concurrent haplotyping and copy-number profiling through genotyping-by-sequencing in bovine embryos
| PRJNA737481 | ENA
Project description:Genome-wide profiling of copy number alterations and DNA methylation in single cells could enable detailed investigation into the genomic and epigenomic heterogeneity of tumor populations. However, current methods to do this require complex sample processing and cleanup steps, lack consistency, or are biased in their genomic representation. Here, we describe a novel single-tube enzymatic method, DNA Analysis by Restriction Enzyme (DARE), to perform deterministic whole genome amplification while preserving DNA methylation information. This method was evaluated on low amounts of DNA and single cells, and provides accurate copy number aberration calling and representative DNA methylation measurement across the whole genome. Single cell DARE is an attractive and scalable approach for concurrent genomic and epigenomic characterization of cells in a heterogeneous population.
2019-08-14 | GSE128560 | GEO