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• Region-Specific Neural Stem Cell Lineages Revealed by Single-Cell RNA-Sequences from Human Embryonic Stem Cells

  During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially be generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development.

  Study phs001205

• colorectal_epigenome

  Three different types of samples were used: 19 normal adjacent, 17 adenoma and 19 colorectal tumor tissue samples. This included 10 pairs of colorectal cancer and normal samples and 1 pair of adenoma-normal samples of the same patient. Tissue specimens were formalin-fixed paraffin-embedded (FFPE). DNA was isolated using the QIAamp FFPE Tissue kit (Qiagen, Hilden, DE) according to the manufacturer’s instructions. The processed DNA was run on the Illumina Human MethylEPIC® v1.0 BeadChip array.

  Dataset EGAD00010002726

• WGS of cell line MMML-seq / MALY-DE tumor_4167452

  This dataset contains the aligned whole genome sequencing data of cell line 380. This cell was established from the peripheral blood of a 15-year-old boy with acute lymphoblastic leukemia at relapse, showing an immature phenotype and carrying an IGH-MYC (t(8;14)) as well as an IGH-BCL2 (t(14;18)) chromosomal translocation. The sequencing was performed on an Illumina X-ten sequencer.

  Dataset EGAD00001004090

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues.

  Dataset EGAD00001002266

• Precision Diagnosis of Neurodevelopmental Disorders in Middle Eastern Populations

  We constructed de novo genome assemblies for six family trios from diverse Middle Eastern ancestries (Sudan, Jordan, Syria, Qatar, and Afghanistan), involving probands with various unresolved neurodevelopmental conditions. We generated high-quality, nearly complete genome assemblies for trios, revealing extended novel sequence impacting known genes, novel HLA/KIR alleles, and strong signals of inbreeding, with runs of homozygosity covering large parts of individual chromosomes. We also identified potential disease variants underlying the unresolved symptoms. Also, the assemblies uncovered unique variation relative to existing references, showing enhanced mapping and variant calling of Middle Eastern genomes. The dataset available through dbGaP includes raw short (Illumina) and long (PacBio) sequencing reads and assembled haplotypes.

  Study phs003917

• Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data

  Genomic translocation events frequently underlie cancer development through generation of gene fusions with oncogenic properties. Identification of such fusion transcripts by transcriptome sequencing might help to discover new potential therapeutic targets. We developed TRUP (Tumor-specimen suited RNA-seq Unified Pipeline (https://github.com/ruping/TRUP), a computational approach that combines split-read and read-pair analysis with de-novo assembly for the identification of chimeric transcripts in cancer specimens. We apply TRUP to RNA-seq data of different tumor types, and find it to be more sensitive than alternative tools in detecting chimeric transcripts, such as secondaryrearrangements in EML4-ALK-positive lung tumors, or recurrent inactivating rearrangements affecting RASSF8.

  Study EGAS00001000659

• Targeted de novo phasing and long-range assembly by template mutagenesis

  Long-range sequencing with low error rate has been challenging. Sequence assembly and phasing usually require a high-quality reference genome for mapping, so working on highly-variable genomic regions or regions with no reference genome information would be difficult. In this study, we describe novel bench protocols and algorithms to obtain ultra-low-error-rate haplotype-phased sequence assemblies of regions 10 KB in length using a short-read sequencing platform that simultaneously solves the above two problems. We accomplish this by imprinting each template strand from a target region with a dense and unique mutation pattern. The mutation process randomly and independently converts ~50% of cytosines to uracils. Short-read sequencing libraries are made from both mutated and unmutated templates. A conservative de Bruijn graph approach seeds an assembly of the mutated templates, which we then extend by mapping paired-end reads. We next partition the template assemblies into two or more haplotypes after using the unmutated sequence library to recover almost all of the mutated bases. The final haplotype is assembled and corrected for residual template mutations and PCR errors. We obtain per-base-error rates below 10 9. We apply this method to a human family, correctly assembling and phasing three genomic intervals, including the highly polymorphic HLA-B gene.

  Dataset EGAD00001008444

• SNV and indel calls from 8921 individuals in the British Autozygosity Populations BioResource dataset

  This includes variant calls (single nucleotide variants and small insertions/deletions) from 8086 (mostly British Pakistani/British Bangladeshi) individuals from the following studies: 1. 5236 British Pakistani/British Bangladeshi adults from East London Genes and Health (ELGH) 2. 2624 British South Asian mothers from Born in Bradford (mostly Pakistani) (BiB) 3. 1061 British South Asian adults from Birmingham (mostly Pakistani) (Birm) All of the Birmingham and most of the Born in Bradford samples were previously sequenced as part of PMID: 26940866. In the sample list file, the columns of interest to most people will be: vcf.id - sample ID from the vcf cohort - which cohort they're in sex.assigned - sex inferred from coverage on the X and Y chromosomes. Individuals for whom this did not match their reported sex have been discarded total, chrX and chrY - coverage within bait regions across all chromosomes, chrX and chrY respectively Mapping was done with bwa-mem and variant calling was carried out with GATK HaplotypeCaller. We removed variant sites for which the following was true: SNPs: "QD < 2.0 || FS > 30 || MQ < 40.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0" Indels: "QD < 2.0 || FS > 30 || ReadPosRankSum < -20.0"

  Dataset EGAD00001005469

• The Role of Germline Mutation and Parental Age in Autism Spectrum Disorders

  <p>We will apply whole genome sequencing of trio families to determine how patterns of germline mutation throughout the genome determine risk for Autism Spectrum Disorder (ASD). We will investigate the nature intrinsic hypermutability and the extrinsic forces, such as paternal age, that influence rates of germline mutation. We will accomplish these goals through the following specific aims: Specific Aim 1 will characterize germline de novo mutations (DNMs) by whole genome sequencing in families. These studies will identify and validate ~8,000 de novo point mutations and structural variants in trios and controls to determine the parent of origin of DNMs. Specific Aim 2 will identify hot spots for germline mutation based on the regional density of DNMs in the genome, and determine the effects of DNA sequence features on rates of mutation. We will determine the association of mutation hotspots with ASD in the discovery sample and in genomic datasets from an independent sample of 2700 cases and 2700 controls. Specific Aim 3 will characterize the effects of extrinsic factors, including parental age and environment, on genome-wide rates of mutation. We will quantify the effect of paternal age on pathogenic and neutral alleles in sperm and investigate whether some DNMs confer a germline selective advantage. The findings of this study will provide fundamental insights into the genetic basis of autism risk and the genetic mechanism of the observed parental age effects in ASD. We will identify genes that confer significant risk for autism, and we will determine how intrinsic properties of the genome interact with extrinsic forces to determining risk for disease in offspring.

  Study phs001164

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385