The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

To assess factors influencing the success of whole genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases across a broad spectrum of disorders in whom prior screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritisation. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease causing variants in 21% of cases, rising to 34% (23/68) for Mendelian disorders and 57% (8/14) in trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, though only four were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis, but also highlight many outstanding challenges.Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use

Purpose: Up to 30% of patients with breast cancer relapse after primary treatment. There are no sensitive and reliable tests to monitor these patients and detect distant metastases before overt recurrence. Here, we demonstrate the use of personalized circulating tumor DNA (ctDNA) profiling for detection of recurrence in breast cancer.Experimental Design: Forty-nine primary patients with breast cancer were recruited following surgery and adjuvant therapy. Plasma samples (n ¼ 208) were collected every 6 months for up to 4 years. Personalized assays targeting 16 variants selected from primary tumor whole-exome data were tested in serial plasma for the presence of ctDNA by ultradeep sequencing (average >100,000X).Results: Plasma ctDNA was detected ahead of clinical or radiologic relapse in 16 of the 18 relapsed patients (sensitivity of 89%); metastatic relapse was predicted with a lead time of up to 2 years (median, 8.9 months; range, 0.5-24.0 months). None of the 31 nonrelapsing patients were ctDNA-positive at any time point across 156 plasma samples (specificity of 100%). Of the two relapsed patients who were not detected in the study, the first had only a local recurrence, whereas the second patient had bone recurrence and had completed chemotherapy just 13 days prior to blood sampling.Conclusions: This study demonstrates that patientspecific ctDNA analysis can be a sensitive and specific approach for disease surveillance for patients with breast cancer. More importantly, earlier detection of up to 2 years provides a possible window for therapeutic intervention. Personalized profiling detects rising ctDNA ahead of clinical relapse. A-E, Plasma levels of ctDNA across serial plasma time points for five patients with breast cancer (one per panel). Mean VAFs are denoted by a dark blue circle, and solid lines represent the average VAF profile over time. The lead time is calculated as the time interval between clinical relapse (red triangle) and molecular relapse (blue triangle). CA 15-3 levels are graphed over time (teal circle), and the baseline levels (32 U/mL) are marked in light blue. F, Summary of percent VAF and number of targets detected at molecular and clinical relapse for all ctDNA-positive samples. Data are from 13 relapsed patients, excluding three patients with only one plasma time point. Coombes et al.

Charcot-Marie-Tooth disease is characterized by length-dependent axonal degeneration with distal sensory loss and weakness, deep-tendon-reflex abnormalities, and skeletal deformities. It is caused by mutations in more than 40 genes. We investigated a four-generation family with 23 members affected by the axonal form (type 2), for which the common causes had been excluded by Sanger sequencing. Exome sequencing of three affected individuals separated by eight meioses identified a single shared novel heterozygous variant, c.917A>G, in DYNC1H1, which encodes the cytoplasmic dynein heavy chain 1 (here, novel refers to a variant that has not been seen in dbSNP131or the August 2010 release of the 1000 Genomes project). Testing of six additional affected family members showed cosegregation and a maximum LOD score of 3.6. The shared DYNC1H1 gene variant is a missense substitution, p.His306Arg, at a highly conserved residue within the homodimerization domain. Three mouse models with different mutations within this domain have previously been reported with age-related progressive loss of muscle bulk and locomotor ability. Cytoplasmic dynein is a large multisubunit motor protein complex and has a key role in retrograde axonal transport in neurons. Our results highlight the importance of dynein and retrograde axonal transport in neuronal function in humans.

Purpose: The purpose of this study was to directly compare mutation profiles in multiple single circulating tumor cells (CTC) and cell-free DNA (cfDNA) isolated from the same blood samples taken from patients with metastatic breast cancer (MBC). We aimed to determine whether cfDNA would reflect the heterogeneity observed in 40 single CTCs.Experimental Design: CTCs were enumerated by CELL-SEARCH. CTC count was compared with the quantity of matched cfDNA and serum CA15-3 and alkaline phosphatase (ALP) in 112 patients with MBC. In 5 patients with !100 CTCs, multiple individual EpCAM-positive CTCs were isolated by DEPArray and compared with matched cfDNA and primary tumor tissue by targeted next-generation sequencing (NGS) of about 2,200 mutations in 50 cancer genes.Results: In the whole cohort, total cfDNA levels and cell counts (!5 CTCs) were both significantly associated with overall survival, unlike CA15-3 and ALP. NGS analysis of 40 individual EpCAMpositive CTCs from 5 patients with MBC revealed mutational heterogeneity in PIK3CA, TP53, ESR1, and KRAS genes between individual CTCs. In all 5 patients, cfDNA profiles provided an accurate reflection of mutations seen in individual CTCs. ESR1 and KRAS gene mutations were absent from primary tumor tissue and therefore likely either reflect a minor subclonal mutation or were acquired with disease progression.Conclusions: Our results demonstrate that cfDNA reflects persisting EpCAM-positive CTCs in patients with high CTC counts and therefore may enable monitoring of the metastatic burden for clinical decision-making.

Long interspersed element 1s (LINE-1s or L1s) are a family of non-long-terminal-repeat retrotransposons that predominate in the human genome. Active LINE-1 elements encode proteins required for their mobilization. L1-encoded proteins also act in trans to mobilize short interspersed elements (SINEs), such as Alu elements. L1 and Alu insertions have been implicated in many human diseases, and their retrotransposition provides an ongoing source of human genetic diversity. L1/Alu elements are expected to ensure their transmission to subsequent generations by retrotransposing in germ cells or during early embryonic development. Here, we determined that several subfamilies of Alu elements are expressed in undifferentiated human embryonic stem cells (hESCs) and that most expressed Alu elements are active elements. We also exploited expression from the L1 antisense promoter to map expressed elements in hESCs. Remarkably, we found that expressed Alu elements are enriched in the youngest subfamily, Y, and that expressed L1s are mostly located within genes, suggesting an epigenetic control of retrotransposon expression in hESCs. Together, these data suggest that distinct subsets of active L1/Alu elements are expressed in hESCs and that the degree of somatic mosaicism attributable to L1 insertions during early development may be higher than previously anticipated.

BACKGROUND Activating mutations in the estrogen receptor 1 (ESR1) gene are acquired on treatment and can drive resistance to endocrine therapy. Because of the spatial and temporal limitations of needle core biopsies, our goal was to develop a highly sensitive, less invasive method of detecting activating ESR1 mutations via circulating cell-free DNA (cfDNA) and tumor cells as a “liquid biopsy.” METHODS We developed a targeted 23-amplicon next-generation sequencing (NGS) panel for detection of hot-spot mutations in ESR1, phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA), tumor protein p53 (TP53), fibroblast growth factor receptor 1 (FGFR1), and fibroblast growth factor receptor 2 (FGFR2) in 48 patients with estrogen receptor-α–positive metastatic breast cancer who were receiving systemic therapy. Selected mutations were validated using droplet digital PCR (ddPCR). RESULTS Nine baseline cfDNA samples had an ESR1 mutation. NGS detected 3 activating mutations in ESR1, and 3 hot-spot mutations in PIK3CA, and 3 in TP53 in baseline cfDNA, and the ESR1 p.D538G mutation in 1 matched circulating tumor cell sample. ddPCR analysis was more sensitive than NGS and identified 6 additional baseline cfDNA samples with the ESR1 p.D538G mutation at a frequency of <1%. In serial blood samples from 11 patients, 4 showed changes in cfDNA, 2 with emergence of a mutation in ESR1. We also detected a low frequency ESR1 mutation (1.3%) in cfDNA of 1 primary patient who was thought to have metastatic disease but was clear by scans. CONCLUSIONS Early identification of ESR1 mutations by liquid biopsy might allow for cessation of ineffective endocrine therapies and switching to other treatments, without the need for tissue biopsy and before the emergence of metastatic disease.

To facilitate broad and convenient integrative visualization of and access to GWAS data, we have created the GWAS Central resource (http://www.gwascentral.org). This database seeks to provide a comprehensive collection of summary-level genetic association data, structured both for maximal utility and for safe open access (i.e., non-directional signals to fully preclude research subject identification). The resource emphasizes on advanced tools that allow comparison and discovery of relevant data sets from the perspective of genes, genome regions, phenotypes or traits. Tested markers and relevant genomic features can be visually interrogated across up to 16 multiple association data sets in a single view, starting at a chromosome-wide view and increasing in resolution down to individual bases. In addition, users can privately upload and view their own data as temporary files. Search and display utility is further enhanced by exploiting phenotype ontology annotations to allow genetic variants associated with phenotypes and traits of interest to be precisely identified, across all studies. Data submissions are accepted from individual researchers, groups and consortia, whereas we also actively gather data sets from various public sources. As a result, the resource now provides over 67 million P-values for over 1600 studies, making it the world's largest openly accessible online collection of summary-level GWAS association information.