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.

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.

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.

Project description:The germ layer concept has been one of the foremost organizing principles in developmental biology, classification, systematics and evolution for 150 years. Of the three germ layers, the mesoderm is found in bilaterian animals but is absent in species in the phyla Cnidaria and Ctenophora, which has been taken as evidence that the mesoderm was the final germ layer to evolve. The origin of the ectoderm and endoderm layers, however, remains unclear with models supporting the antecedence of each as well as a simultaneous origin. We hypothesized that global analysis of gene expression in each layer throughout development may resolve the early events of animal evolution. Here, we determine the temporal and spatial components of gene expression spanning embryonic development for all C. elegans genes and use it to determine the evolutionary age of the germ layers. The gene expression programs of the mesoderm is generally induced after the ectoderm and endoderm germ layers, thus making it the last germ layer to both evolve and develop. Strikingly, the C. elegans endoderm and ectoderm expression programs do not co-induce; rather the endoderm activates earlier. We also observed early expression of endoderm orthologs during the embryology of Xenopus tropicalis, Nematostella vectensis, and the sponge Amphimedon queenslandica. Querying for the phylogenetic ages of specifically expressed genes revealed that the endoderm is comprised of older genes, supporting its antecedence among the germ layers. Taken together, we propose that the endoderm program has retained the feeding functions of the last common ancestor with the choanoflagellates, thus allowing for the specialization of an ectoderm germ layer. Our work reveals that the evolutionary appearance of the germ layers continues to constrain regulatory networks in metazoans. Two temporal assays of C. elegans embryonic development, starting at the zygote: (a) Embryos collected at fixed (~10 minute) time intervals. (b) Embryo segregates, up to five lines of blastomeres, isolated in reference to mitotic events. There were 184 samples in total, representing 100 distnict data points.

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Concurrent whole-genome haplotyping and copy number profiling of single cells

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