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• Genome-Wide Association Study of Preterm Birth

  Preterm birth (PTB, born before 37 weeks of gestation) is a leading cause of neonatal mortality and post-natal morbidity. PTB affects one in nine all live births in the U.S. Notably, the highest rate of PTB occurs among African Americans (one in six). PTB is a complex trait, likely determined by multiple environmental and genetic factors and their interactions. We demonstrated strong familial aggregation of preterm and low birthweight in the US Blacks and Whites (Wang et al, NEJM, 1995) and conducted the largest candidate gene study of preterm birth at that time (Hao et al, HMG, 2004). We showed that a subset of mothers with certain metabolic gene variants are particularly vulnerable to the adverse effects of cigarette smoking on low birthweight and preterm births (Wang et al, JAMA, 2002). We also published a number of papers that examined the effect of maternal pre-pregnancy BMI, micronutrient status, stress and environmental toxins on the risk of preterm birth and related conditions. This project, supported by a grant from the NICHD (2R01HD41702, PI, Xiaobin Wang), aimed to conduct a genome-wide association study (GWAS) and apply advanced statistical methods to identify susceptibility loci of PTB in a predominantly urban low-income African American sample, a subset of the Boston Birth Cohort. PUBLIC HEALTH REVELANCE: We anticipate that this study will lead to the identification of novel genetic loci of PTB and gene-environment interactions. Such findings not only will provide important insights into mechanisms leading to PTB, but also may help identify women at high-risk of PTB, which in turn, may lead to the development of early and targeted interventions that can prevent PTB or mitigate the severity and consequences of PTB.

  Study phs000332

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• L1-Architect Project Dataset

  Tumours with high and ultrahigh rates of somatic retrotransposition studied in the publication by Zumalave et al. titled Synchronous L1 retrotransposition events promote chromosomal crossover early in human tumorigenesis

  Dataset EGAD50000000607

• RNAseq of LC2AD with AD80 or DMSO

  RNAseq of LC2AD with AD80 or DMSO Plenker et al., Mechanistic insight into RET kinase inhibitors targeting the DFG-out conformation in RET-rearranged cancer

  Dataset EGAD00001003316

• Ovarian cancer sequencing dataset

  Sequencing data from patients with Ovarian cancer. Data utilised in the 'Enhanced detection of circulating tumor DNA by fragment size analysis' manuscript (Mouliere et al, 2018)

  Dataset EGAD00001004939

• Neuroblastoma Cell Line Circle-seq Data

  This dataset comprises Circle-seq data for 12 neuroblastoma cell lines supporting Koche et al. Extrachromosomal circular DNA drives oncogenic genome remodeling in neuroblastoma (2020).

  Dataset EGAD00001006579

• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• 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