Illumina SNP and CNV data for the HuRef individual
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE20284 | GEO | 2013/02/12
SECONDARY ACCESSION(S): PRJNA189290
REPOSITORIES: GEO
Similar Datasets
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual.
2013-02-12 | GSE20275 | GEO
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual. An Illumina SNP array experiment was performed according to the manufacturer's directions on DNA extracted from a lymphoblastoid cell line (HuRef).
2013-02-12 | E-GEOD-20284 | biostudies-arrayexpress
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual.
2013-02-12 | GSE20289 | GEO
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual. An Affymetrix SNP array experiment was performed according to the manufacturer's directions on DNA extracted from a lymphoblastoid cell line (HuRef). Copy number analysis of Affymetrix 6.0 SNP arrays was performed for the HuRef sample. The HuRef sample was run in a batch of 50 control samples, which were used as baseline for calling CNVs.
2013-02-12 | E-GEOD-20275 | biostudies-arrayexpress
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual.
2013-02-12 | GSE20288 | GEO
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual.
2013-02-12 | GSE20287 | GEO
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual. The HuRef genomic DNA (from lymphoblastoid cell line) was co-hybridized with the female sample NA15510 (from lymphoblastoid cell line) from the Polymorphism Discovery Resources. The NimbleGen platform consists of 20 NimbleGen HD2 chips, each containing 2.1M probes, and each chip is further subdivided into 3 equal-sized subarrays containing about 726K probes. The probes target the NCBI Build 36 genome, with the exception that no homology filter was applied, allowing coverage of segmentally duplicated regions.
2013-02-12 | E-GEOD-20289 | biostudies-arrayexpress
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual. CGH experiments were performed with genomic DNA extracted from the HuRef and six HapMap lymphoblastoid cell lines, hybridized against the reference NA10851. A dye-swap experiment was performed for each experiment. The custom CGH microarray contains probes that target novel sequences that are not on the NCBI reference build 35. Instead, the probes target scaffold sequences that are unique to the Celera R27C assembly.
2013-02-12 | E-GEOD-20287 | biostudies-arrayexpress
Project description:The ideal genome sequence for medical interpretation is complete and diploid, capturing the full spectrum of genetic variation. Toward this end, there has been progress in discovery of single nucleotide polymorphism (SNP) and small (<10bp) insertion/deletions (indels), but annotation of larger structural variation (SV) including copy number variation (CNV) has been less comprehensive, even with available diploid sequence assemblies. We applied a multi-step sequence and microarray-based analysis to identify numerous previously unknown SVs within the first genome sequence reported from an individual. Agilent array CGH experiment was performed according to the manufacturer's directions on DNA extracted from lymphoblastoid cell lines. HuRef genomic DNA was co-hybridized with female sample NA15510 from the Polymorphism Discovery Resource. No replicate nor dye swap was done. The Agilent 24 million features CGH array set was designed with 23.5 million 60-mer oligonucleotide probes tiled along the NCBI Build 36 assembly.
2013-02-12 | E-GEOD-20288 | biostudies-arrayexpress
Project description:To understand the population genetics of structural variants (SVs), and their effects on phenotypes, we developed an approach to mapping SVs, particularly transpositions, segregating in a sequenced population, and which avoids calling SVs directly. The evidence for a potential SV at a locus is indicated by variation in the counts of short-reads that map anomalously to the locus. These SV traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between an SV trait at one locus and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3x) population sequence data from 488 recombinant inbred Arabidopsis genomes, we identified 6,502 segregating SVs. Remarkably, 25% of these were transpositions. Whilst many SVs cannot be delineated precisely, PCR validated 83% of 44 predicted transposition breakpoints. We show that specific SVs may be causative for quantitative trait loci for germination, fungal disease resistance and other phenotypes. Further we show that the phenotypic heritability attributable to sequence anomalies differs from, and in the case of time to germination and bolting, exceeds that due to standard genetic variation. Gene expression within SVs is also more likely to be silenced or dysregulated, as inferred from RNA-seq data collected from a subset of just over 200 of the MAGIC lines. This approach is generally applicable to large populations sequenced at low-coverage, and complements the prevalent strategy of SV discovery in fewer individuals sequenced at high coverage.
2017-02-10 | GSE94107 | GEO