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• A method for multiplexed full-length single-molecule sequencing of the human mitochondrial genome

  Study EGAS00001006280

• Identification of IQCH as a calmodulin-associated protein required for sperm motility in humans

  Study EGAS00001007423

• DAC - A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Dac EGAC00001003530

• Single-cell dissection of the immune response after a myocardial infarction

  Study EGAS00001007021

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line RNA-Seq

  Study EGAS00001006802

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line WXS

  Study EGAS00001006800

• Center for Common Disease Genomics [CCDG] - Cardiovascular: The Genetics of Atrial Fibrillation

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for UWO Genetic Investigation of Supraventricular Tachycardias.Patients confirmed to possess a supraventricular tachycardia and/or an accessory pathway at the time of invasive electrophysiology study at the London Health Sciences Centre, London, Ontario, Canada were eligible for enrollment. Potential supraventricular tachycardias included atrioventricular nodal reentrant tachycardia (AVNRT), atrioventricular reentrant tachycardia (AVRT), atrial tachycardia, junctional tachycardia, atriofascicular tachycardia, nodofascicular tachycardia, and nodoventricular tachycardia. Patients that did not have inducible supraventricular tachycardia, but had an accessory pathway that conducted antegrade, retrograde, or both, were also eligible for enrollment. All patients additionally underwent, at minimum, a clinical history, physical examination, 12-lead ECG, and echocardiogram. Study participants provided informed written consent under a protocol approved by the research ethics board of Western University.Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data For questions about availability contact help@lists.anvilproject.org.

  Study phs002811

• Genes for Non-Syndromic Congenital Heart Disease

  Congenital heart defects (CHDs) are the most common serious birth defect and a leading cause of infant mortality. Affected individuals who survive infancy require substantial medical care and experience lifelong morbidity and early mortality. Despite their prevalence and impact upon public health, the etiology of CHDs is poorly understood. Our long-term goal is to better define the genetic basis of CHDs and using this information, develop preventive measures and provide precise medical management based on genotype. As CHDs are a heterogeneous group of conditions, we have focused our studies on cases with conotruncal heart defects (CTDs) that comprise at least 36% of all CHDs and are a prominent feature of the 22q11.2 deletion syndrome (22q11DS). We have conducted both SNP- and CNV-based genome-wide association studies as part of our previous and current P01 (HD070454). Our current analyses of genes and gene-sets provide new insights regarding the contribution of common and rare inherited genetic variants to CTDs. Specifically, based on the results from our studies as well as recently published findings, we hypothesize that: (1) CTDs are influenced by the full range of genetic variability (rare to common; de novo and inherited) in relevant gene-sets; (2) the number of disease-related variants within these gene-sets varies directly with CTD severity; and (3) gene-sets associated with CTDs in nonsyndromic individuals are also associated with CTDs in individuals with the 22q11DS. To augment our existing cohorts and thus substantially improve the statistical power of our proposed analyses, application was made to complete array genotyping of a set of patients with CTDs and in particular, those with mild disease represented by isolated aortic arch anomalies. The new cases with CTD and some with an isolated aortic arch anomaly were ascertained at the Children's Hospital of Philadelphia (CHOP) while some of the cases with isolated aortic arch anomalies were ascertained by the Pediatric Cardiac Genomics Consortium (PCGC). A small group of cases with left-sided obstructive lesions from CHOP were included to combine with our existing datasets to serve as a comparison to those with CTD. The additional genotype data will augment the statistical power of the proposed common variant analyses. We anticipate that this work will reduce the gaps in our understanding of CTDs by identifying an explicit set of genes associated with CTD-risk by way of common variants. This work will also help define the genetic architecture for the full clinical spectrum of these common birth defects.

  Study phs002059

• Assessment of RNA-Seq Sample Preparation Methodology

  The goal of this study was two-fold, to determine if common purification techniques have any effect on downstream differential expression analysis and to evaluate combinations of alignment and differential expression software for reliability. To this end, blood was collected from three individuals and pooled during and after extraction. After pooling and mixing was completed, samples were divided into three aliquots for testing. The first aliquot was a control and not purified or concentrated. It was diluted to produce samples of varying concentrations for testing. The second aliquot was diluted to 20 ng/μL and used to test six different variations on the AMPure XP bead purification procedure. The last aliquot was also diluted to varying concentrations of 60, 30, and 9.6 ng/μL and purified using MinElute columns. Samples were submitted for total RNA-Seq library preparation and sequencing. Library preparation was performed using the TruSeq Stranded Total RNA with Ribo-Zero Globin kit (20020612, Illumina Inc.), and 2x150 bp PE sequencing was done on an Illumina NovaSeq 6000 with the S4 reagent kit. Comparisons were made between methods (AMPure vs. unpurified, AMPure vs. MinElute, MinElute vs. unpurified) to assess the effects of purification method on downstream differential expression. Comparisons were also made within methods using the varying concentrations tested for unpurified samples and for MinElute purified samples to assess the effects of concentration on differential expression. Variations of the AMPure procedure were also compared to assess the effectiveness of the variations tested in comparison to the unmodified procedure. A subset of samples was selected for use with alignment and differential expression package comparison. Unpurified high concentration samples eluted in RNAse-free water were compared to unpurified high concentration samples eluted in BR5, a buffer from the PAXgene blood miRNA kit, with the expectation that there should be no or very few differentially expressed genes. Unpurified high concentration samples eluted in RNAse-free water were also compared to unpurified low concentration samples also eluted in RNAse-free water, with possibly a small number of differentially expressed genes anticipated. A third dataset of simulated RNA-seq data was created with a known rate of differential expression. These files were aligned using Bowtie2, HISAT2, kallisto, RSEM, Rsubread, Salmon, and STAR. Results were then analyzed for differential expression using ALDEx2, baySeq, DEGseq, DESeq2, edgeR, limma, NOISeq, PoissonSeq, and SAMseq. Differential expression results of all three comparisons were evaluated to determine which combinations provided the most reliable results for both real and simulated data.

  Study phs003001

• NSIGHT BabySeq Project

  The Genomic Sequencing for Childhood Risk and Newborn Illness (BabySeq Project) is a research study exploring the use of genomic sequencing in newborns. The National Institutes of Health is funding this study. Investigators enrolled 240 healthy infants and their parents from the Brigham and Women's Hospital (BWH) Well Newborn Nursery and 240 sick infants and their parents at Boston Children's Hospital (BCH) or the BWH Neonatal Intensive Care Unit (NICU). A small blood sample was taken from each infant and genome sequencing may have been performed. Whole-exome (WES) was performed at the Broad Institute. Six weeks later, the results were returned and explained. Over 12 months, the investigators studied the experiences of parents and pediatricians of infants who receive sequencing to help understand how best to use genomics in pediatric care. Parents were surveyed at four points over the 12 months after enrollment: baseline, immediately post-disclosure (approximately 6 weeks after enrollment), 3 months post-disclosure, and at 10 months post-disclosure. Primary outcome measures included: (1) downstream health care costs attributable to BabySeq Project disclosure measured as days of inpatient care; (2) Parents' distress using validated scales and a novel item assessing blame; (3) parent-child relationship using validated scales; (4) Parents' relationship using validated and novel measures of marital satisfaction; (5-9) downstream health care utilization attributable to BabySeq project disclosure measured as the number of health care provider visits, per-patient counts for number of medications at 10 months, number of emergency room visits, number of outpatient lab tests, and per-patient means for healthcare costs in U.S. dollars. A secondary outcome was whether there was a change in perceived utility toward genomic sequencing. Findings of BabySeq include: (1) interest in newborn genomic testing is high among parents of healthy children and the majority of couples had similar levels of interest; (2) parents reported several motivations to receive and reasons to decline adult-onset only results from newborn sequencing; (3) 88% of newborns had at least one recessive carrier variant that could be relevant to their parents' future reproductive planning; (4) 5% of babies had an atypical pharmacogenomic variant related to how they might process medications used in childhood; (5) parent surveys using validated measures showed no evidence that newborn genomic sequencing caused increased psychological distress, even if the baby had a disease risk identified; and (6) 11% of newborn babies in the study had unanticipated monogenic disease risks.

  Study phs002093