Genome-wide haplotyping of human single cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE17318 | GEO | 2012/10/01
SECONDARY ACCESSION(S): PRJNA119043
REPOSITORIES: GEO
Similar Datasets
Project description:A method to infer genome-wide haplotypes from the analysis of one or two single (human) cells has tremendous applicative value. It would revolutionize not only preimplantation genetic diagnosis of in vitro fertilized human embryos in the clinic, but also animal breeding programs by enabling genome-wide quantitative trait loci selection at the embryonic level. In addition, it allows to further scrutinize drivers of haplotype diversity, mainly meiotic homologous recombination as well as somatic (homologous) recombination processes that occur often during (human) tumorigenesis. We developed a generic approach to type genome-wide single nucleotide polymorphisms in single human cells and to reconstruct genome-wide haplotypes of single or dual cell derived genotypes. Genome-wide sequences of syntenic alleles were determined for EBV-transformed lymphoblastoid cells as well as human blastomeres. To this end, multiple displacement amplified DNA samples of single cells were hybridized to Affymetrix 250K SNP-arrays. Different algorithmic designs were subsequently developed to assess from the single cell-derived SNP-probe intensities the sequence of syntenic alleles and to pinpoint accurately the majority of parental homologous recombination sites using a linkage-based approach. In total 12 amplified single human lymphoblastoid cell DNA samples, 3 amplified single human blastomere DNA samples and 19 non-amplified genomic DNA samples extracted from blood were analyzed by 250K Nsp I SNP arrays (GEO accession number GPL3718). The non-amplified genomic DNA samples extracted from blood were derived from 19 different persons belonging to 4 different families. The sample names of these 19 samples are respectively Family1_Individual1, Family1_mother, Family1_father, Family1_MaternalGrandmother, Family2_Individual2, Family2_mother, Family2_father, Family2_MaternalGrandmother, Family2_MaternalGrandfather, Family3_Individual3, Family3_Individual4, Family3_mother, Family3_father, Family3_MaternalGrandmother, Family3_MaternalGrandfather, Family4_mother, Family4_father, Family4_PaternalGrandmother, Family4_PaternalGrandfather. These 19 non-amplified genomic DNA samples extracted from blood were genotyped using the dynamic model algorithm embedded in the M-bM-^@M-^XGeneChip Genotyping Analysis Software (GTYPE) version 4.1 (Affymetrix)M-bM-^@M-^Y using a homozygous and heterozygous calling threshold of 0.12. The 12 amplified single lymphoblastoid cell DNA samples were derived from Epstein Barr virus transformed lymphoblastoid cell lines (EBV-line) of four different persons. Three amplified single lymphoblastoid cell DNA samples from individual M-bM-^@M-^\Family1_Individual1M-bM-^@M-^], three amplified single lymphoblastoid cell DNA samples from individual M-bM-^@M-^\Family2_Individual2M-bM-^@M-^], three amplified single lymphoblastoid cell DNA samples from individual M-bM-^@M-^\Family3_Individual3M-bM-^@M-^] and three amplified single lymphoblastoid cell DNA samples from individual M-bM-^@M-^\Family3_Individual4M-bM-^@M-^]. The samples names of these 12 are respectively: Family1_Individual1_SingleCell1, Family1_Individual1_SingleCell2, Family1_Individual1_SingleCell3, Family2_Individual2_SingleCell1, Family2_Individual2_SingleCell2, Family2_Individual2_SingleCell3, Family3_Individual3_SingleCell1, Family3_Individual3_SingleCell2, Family3_Individual3_SingleCell3, Family3_Individual4_SingleCell1, Family3_Individual4_SingleCell2, Family3_Individual4_SingleCell3. These 12 amplified single lymphoblastoid cell DNA samples were genotyped using (1) the dynamic model algorithm embedded in the M-bM-^@M-^XGeneChip Genotyping Analysis Software (GTYPE) version 4.1 (Affymetrix)M-bM-^@M-^Y using a homozygous and heterozygous calling threshold of 0.12, (2) the BRLMM algorithm within the M-bM-^@M-^XGenotyping console 3.0.1M-bM-^@M-^Y software (Affymetrix) using a scoring threshold of 0.1 and (3) the Birdseed algorithm of the APT-1.10.1 package (Affymetrix Power Tools) using the M-bM-^@M-^Xbirdseed-devM-bM-^@M-^Y command which is the most recently incorporated development version of birdseed from The Broad Institute (http://www.broadinstitute.org/mpg/birdsuite/birdseed.html). The 3 amplified single human blastomere DNA samples were derived from three different human blastomeres that belong to the same in vitro fertilized embryo. This embryo was conceived in vitro by using sperm of person M-bM-^@M-^\Family4_fatherM-bM-^@M-^] and an oocyte from person M-bM-^@M-^\Family4_motherM-bM-^@M-^]. The sample names of these 3 amplified single blastomere DNA samples are respectively: Family4_Blastomere1, Family4_Blastomere2, Family4_Blastomere3. These 3 amplified single human blastomere DNA samples were genotyped using the dynamic model algorithm embedded in the M-bM-^@M-^XGeneChip Genotyping Analysis Software (GTYPE) version 4.1 (Affymetrix)M-bM-^@M-^Y using a homozygous and heterozygous calling threshold of 0.12.
2012-10-01 | E-GEOD-17318 | biostudies-arrayexpress
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: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. 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:Many loci in the human genome harbor complex genomic structures that can result in susceptibility to genomic rearrangements leading to various genomic disorders. Nephronophthisis 1 (NPHP1, MIM# 256100) is an autosomal recessive disorder that can be caused by defects of NPHP1; the gene maps within the human 2q13 region where low copy repeats (LCRs) are abundant. Loss of function of NPHP1 is responsible for approximately 85% of the NPHP1 cases - about 80% of such individuals carry a large recurrent homozygous NPHP1 deletion that occurs via non-allelic homologous recombination (NAHR) between two flanking directly oriented ~45 kb LCRs. Published data revealed a non-pathogenic inversion polymorphism involving the NPHP1 gene flanked by two inverted ~358 kb LCRs. Using optical mapping and array-comparative genomic hybridization, we identified three potential novel structural variant (SV) haplotypes at the NPHP1 locus that may protect a haploid genome from genomic instability and NPHP1 deletion. Inter-species comparative genomic analyses among primate genomes revealed massive genomic changes during evolution. The aggregated data suggest that dynamic genomic rearrangements occurred historically within the NPHP1 locus and generated SV haplotypes observed in the human population today, which may have differential susceptibility to the NPHP1 deletion within a personal genome. Our study documents diverse SV haplotypes at a complex LCR-laden human genomic region. Comparative analyses provide a model for how this complex region arose during primate evolution, and studies among humans reflect the possibility that intra-species polymorphism may potentially modulate an individual’s susceptibility to acquiring disease-associated alleles.
2015-11-30 | GSE73962 | 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. Here we provide two sample sets, including (1) a reference family delivering samples applied for the development and optimization of single-cell genotyping, QC-metrics, haplarithmisis and the siCHILD algorithm. 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 also isolated, of which three were whole-genome amplified using MDA and three using PicoPlex. These multi-cell genomic DNA samples and single-cell WGA-products were hybridized to Illumina HumanCytoSNP12-v2.1 SNP-arrays following: (i) the protocol as recommended by the company and/or (ii) a modified rapid protocol as described below. Subsequently, the SNP-probe signals were interpreted by two different genotyping algorithms (GenCall and GenoSNP). Based on overall performance, we decided to use GenCall for interpreting Illumina SNP-probe signals of single-cell and multi-cell DNA samples. (2) A set of 12 families undergoing genetic diagnosis (for Mendelian disorders or translocation chromosomes) of preimplantation embryos following in vitro fertilization. In general, each family delivers genomic DNA samples isolated from peripheral blood of the two parents as well as a sibling and/or other close relatives; the specific kinships for each family are given in the 'description' column. In addition, of each family single blastomeres biopsied from preimplantation embryos obtained via in vitro fertilization of the parental gametes are also provided. All single-cell genomes were amplified by MDA. All the samples were hybridized to Illumina HumanCytoSNP12-v2.1 SNP-arrays following the rapid protocol. This data was used for clinical validation of the siCHILD algorithm.
2015-05-15 | E-GEOD-60909 | biostudies-arrayexpress
Project description:HS-10502 is a Poly(ADP-ribose) polymerase 1 (PARP1)-specific selective inhibitor. The purpose if this study is to assess the safety, tolerability, pharmacokinetics (PK), and efficacy of HS-10502 in subjects with homologous recombination repair (HRR) gene mutant or homologous recombination deficiency (HRD) positive advanced solid tumors.
| 9330 | ecrin-mdr-crc
Project description:A Phase 2, open-label, single-arm trial to evaluate the response of rucaparib in participants with various solid tumors and with deleterious mutations in Homologous Recombination Repair (HRR) genes.
| 2322588 | ecrin-mdr-crc
Project description:The identification of multiple signals at individual loci could explain additional phenotypic variance ('missing heritability') of common traits, and help identify causal genes. We examined gene expression levels as a model trait because of the large number of strong genetic effects acting in cis. Using expression profiles from 613 individuals, we performed genome-wide single nucleotide polymorphism (SNP) analyses to identify cis-expression quantitative trait loci (eQTLs), and conditional analysis to identify second signals. We examined patterns of association when accounting for multiple SNPs at a locus and when including additional SNPs from the 1000 Genomes Project. We identified 1298 cis-eQTLs at an approximate false discovery rate 0.01, of which 118 (9%) showed evidence of a second independent signal. For this subset of 118 traits, accounting for two signals resulted in an average 31% increase in phenotypic variance explained (Wilcoxon P< 0.0001). The association of SNPs with cis gene expression could increase, stay similar or decrease in significance when accounting for linkage disequilibrium with second signals at the same locus. Pairs of SNPs increasing in significance tended to have gene expression increasing alleles on opposite haplotypes, whereas pairs of SNPs decreasing in significance tended to have gene expression increasing alleles on the same haplotypes. Adding data from the 1000 Genomes Project showed that apparently independent signals could be potentially explained by a single association signal. Our results show that accounting for multiple variants at a locus will increase the variance explained in a substantial fraction of loci, but that allelic heterogeneity will be difficult to define without resequencing loci and functional work. Gene expression data was determined of peripheral blood samples (n=705) from InChianti cohort.
2013-06-21 | E-GEOD-48152 | biostudies-arrayexpress
Project description:Rapid advances in high-throughput DNA sequencing technologies are accelerating the pace of research into personalized medicine. While methods for variant discovery and genotyping from whole genome sequencing (WGS) datasets have been well established, linking variants together into a single haplotype remains a challenge. An understanding of complete haplotypes of an individual will help clarify the consequences of inheriting multiple alleles in combination, identify novel disease associations, and augment studies of gene regulation. Although numerous methods have been developed to reconstruct haplotypes from WGS data, chromosome-span haplotypes at high resolution have been difficult to obtain. Here we present a novel method to accurately reconstruct chromosome-span haplotypes from proximity-ligation and DNA shotgun sequencing. We demonstrate the utility of this approach in producing high-resolution chromosome-span haplotype phasing in mouse and human. While proximity-ligation based methods were originally designed to investigate spatial organization of the genome, our results lend support for their use as a general tool for haplotyping in the future.
2013-11-03 | GSE48592 | GEO