Journal: PLoS Biology

Article Title: The Diploid Genome Sequence of an Individual Human

doi: 10.1371/journal.pbio.0050254

Figure Lengend Snippet: (A) Three-generation pedigree showing the relation of ancestors to study DNA sample. The donor is identified in red. (B) Cluster analysis based on 750 SNP genotype information to infer the ancestry of the HuRef donor. The figure shows the proportion of membership of the HuRef donor (yellow) to three pre-defined HapMap populations (CEU = Northern and Western Europe, YRI = Yoruban, Ibadan, Nigeria, and JPT+CHB = Japanase, Tokyo, and Han Chinese, Beijing). The results indicate that the HuRef donor clusters with 99.5% similarity to the samples of northern and western European ancestry.

Article Snippet: To evaluate the accuracy and validity of SNP calling from the sequencing reads, the donor DNA was interrogated using hybridization-based SNP microarrays: the Affymetrix Mapping 500K Array Set, which targets 500,566 SNP markers, and the Illumina HumanHap650Y Genotyping BeadChip, which targets 655,362 SNPs.

Techniques: Northern Blot, Western Blot

Journal: PLoS Biology

Article Title: The Diploid Genome Sequence of an Individual Human

doi: 10.1371/journal.pbio.0050254

Figure Lengend Snippet: Sequences from the HuRef donor that had no match based on the one-to-one mapping or BLAST when compared to the NCBI Human reference genome were tested by FISH. Fosmids were used as probes and the experiments were run, using Coriell DNA, to confirm the localization of the contigs or to map contigs with no prior mapping information. Shown here are four representative results. (A) An insertion at 7q22 where the FISH confirmed the HuRef mapping, (B) FISH result confirming the mapping of a sequence extending into a gap at 1p21. (C) Localization of a contig with no prior mapping information to chromosomal band 1q42. (D) An example of euchromatic-like sequence with no prior mapping information, which hybridizes to multiple centromeric locations.

Article Snippet: To evaluate the accuracy and validity of SNP calling from the sequencing reads, the donor DNA was interrogated using hybridization-based SNP microarrays: the Affymetrix Mapping 500K Array Set, which targets 500,566 SNP markers, and the Illumina HumanHap650Y Genotyping BeadChip, which targets 655,362 SNPs.

Techniques: Sequencing

Journal: Leukemia & lymphoma

Article Title: OVERCOMING MULTIPLE MYELOMA DRUG RESISTANCE IN THE ERA OF CANCER “OMICS”

doi: 10.1080/10428194.2017.1337115

Figure Lengend Snippet: “Omics” technologies used in preclinical and clinical studies

Article Snippet: By using molecular profiles to understand disease mechanisms, predict drug response and patient relapse, “omics” data can be used to guide pre-clinical drug development and tailor personalized treatments for each individual patient and disease. table ft1 table-wrap mode="anchored" t5 Table 1. caption a7 Omics Approach Omics Technology Source Material Readout Application Preclinical Clinical WGS, WES Genomics Genomic DNA (Germline) WGS: Sequence of entire chromosomal and mitochondrial DNA WES: Sequence of all exomes in genome Discover new mechanisms of drug resistance, biomarker discovery Patient risk stratification, predict response to therapy, guide therapeutic decisions Cancer genome sequencing Genomic DNA (Tumour) Mutational profile of cancer SNP array, CNV microarray Genomic DNA (Germline or Tumour) Unbiased association of genotype and phenotype Identification of genetic variation associated with response and/or adverse events to treatment RNA Seq, RNA microarray Transcriptomics mRNA (cDNA) Gene expression profile, disease associated genes, chemoresistance- associated genes Monitor changes in mutational landscape of cancer, predict response to therapy, guide therapeutic decisions Protein analysis by LC-MS/MS, SILAC-MS, ITRAQ-MS Proteomics Proteins Protein maps and predicted networks, disease-associated proteins, chemoresistance-associated proteins Predict treatment response, guide therapeutic decisions, monitor treatment response and relapse Metabolome analysis by LC-MS/MS, NMR, ion-mobility spectrometry, Raman spectroscopy Metabolomics Metabolites Metabolite profiles in cancer, tissues, and body fluids Genome-wide DNA methylation assays, miRNA array, Histone modification assays Epigenomics DNA, proteins DNA methylation, miRNAs, histone modifications High-throughput screen (knockdown/knockout shRNA/CRISPR-Cas9 screens, overexpression screens, drug screens) Genomics, Multi-omics Cells, proteins, embryo Phenotype (i.e. survival, proliferation, chemoresistance), biochemical, etc... NA Open in a separate window WGS: whole genome sequencing; WES: whole exome sequencing; SNP: single nucleotide polymorphism; CNV: copy number variant; LC-MS/MS: liquid chromatography-tandem mass spectrometry; miRNA: microRNA; NMR: nuclear magnetic resonance; shRNA: short hairpin RNA; CRISPR: clustered regularly interspaced short palindromic repeats “Omics” technologies used in preclinical and clinical studies Indeed, recent advances in high-throughput “omics” techniques afford us an unprecedented opportunity to understand drug resistance at the genomic, transcriptomic, and proteomic level.

Techniques: Sequencing, Biomarker Discovery, Microarray, RNA Sequencing, Gene Expression, Multiplex sample analysis, Ion-Mobility Spectrometry, Raman Spectroscopy, Genome Wide, DNA Methylation Assay, Modification, Knockdown, shRNA, Over Expression