The Aquatic Symbiosis Genomics Project: probing the evolution of symbiosis across the Tree of Life

We present the Aquatic Symbiosis Genomics Project, a global collaboration to generate high quality genome sequences for a wide range of eukaryotes and their microbial symbionts. Launched under the Symbiosis in Aquatic Systems Initiative of the Gordon and Betty Moore Foundation, the ASG Project brings together researchers from across the globe who hope to use these reference genomes to augment and extend their analyses of the dynamics, mechanisms and environmental importance of symbioses. Applying large-scale, high-throughput sequencing and assembly technologies, the ASG collaboration will assemble and annotate the genomes of 500 symbiotic organisms – both the “hosts” and the microbial symbionts with which they associate. These data will be released openly to benefit all who work on symbioses, from conservation geneticists to those interested in the origin of the eukaryotic cell. The Aquatic Symbiosis Genomics Project is a worldwide effort to find the genome sequences of a variety of organisms and their microbial partners living in water. Supported by the Gordon and Betty Moore Foundation, this project involves scientists from around the world. The genome sequences will help scientists to better understand how these organisms interact with each other and their environment. The project will use advanced technology to map out the genes of 500 pairs of host organisms and their microbial symbionts. This information will be freely available, helping everyone from researchers studying species conservation to those exploring the beginnings of complex cell life

Regulation of BRCA1 expression and its relationship to sporadic breast cancer

Germ-line mutations in the BRCA1 tumour suppressor gene contribute to familial breast tumour formation, but there is no evidence for direct mutation of the BRCA1 gene in the sporadic form of the disease. In contrast, decreased expression of the BRCA1 gene has been shown to be common in sporadic tumours, and the magnitude of the decrease correlates with disease progression. BRCA1 expression is also tightly regulated during normal breast development. Determining how these developmental regulators of BRCA1 expression are co-opted during breast tumourigenesis could lead to a better understanding of sporadic breast cancer aetiology and the generation of novel therapeutic strategies aimed at preventing sporadic breast tumour progression

Fanconi anemia genes are highly expressed in primitive CD34(+ )hematopoietic cells

BACKGROUND: Fanconi anemia (FA) is a complex recessive genetic disease characterized by progressive bone marrow failure (BM) and a predisposition to cancer. We have previously shown using the Fancc mouse model that the progressive BM failure results from a hematopoietic stem cell defect suggesting that function of the FA genes may reside in primitive hematopoietic stem cells. METHODS: Since genes involved in stem cell differentiation and/or maintenance are usually regulated at the transcription level, we used a semiquantitative RT-PCR method to evaluate FA gene transcript levels in purified hematopoietic stem cells. RESULTS: We show that most FA genes are highly expressed in primitive CD34-positive and negative cells compared to lower levels in more differentiated cells. However, in CD34(- )stem cells the Fancc gene was found to be expressed at low levels while Fancg was undetectable in this population. Furthermore, Fancg expression is significantly decreased in Fancc -/- stem cells as compared to wild-type cells while the cancer susceptibility genes Brca1 and Fancd1/Brac2 are upregulated in Fancc-/- hematopoietic cells. CONCLUSIONS: These results suggest that FA genes are regulated at the mRNA level, that increased Fancc expression in LTS-CD34(+ )cells correlates with a role at the CD34(+ )differentiation stage and that lack of Fancc affects the expression of other FA gene, more specifically Fancg and Fancd1/Brca2, through an unknown mechanism

Caretaker Brca1: keeping the genome in the straight and narrow

Inheritance of germline BRCA1 mutations is associated with a high risk of breast and ovarian cancers. A multitude of cellular functions has been ascribed to BRCA1, including transcription activation and various aspects of DNA repair. So far, indirect evidence has indicated a role for BRCA1 in the repair of double-strand breaks. Recently, an elegant gene targeting design was used to provide definitive evidence that BRCA1 promotes homologous recombination and limits nonhomologous mutagenic repair processes. This reaffirms the role of BRCA1 as caretaker in preserving genomic integrity

BRCA1 and BRCA2 as molecular targets for phytochemicals indole-3-carbinol and genistein in breast and prostate cancer cells

Indole-3-carbinol (I3C) and genistein are naturally occurring chemicals derived from cruciferous vegetables and soy, respectively, with potential cancer prevention activity for hormone-responsive tumours (e.g., breast and prostate cancers). Previously, we showed that I3C induces BRCA1 expression and that both I3C and BRCA1 inhibit oestrogen (E2)-stimulated oestrogen receptor (ER-α) activity in human breast cancer cells. We now report that both I3C and genistein induce the expression of both breast cancer susceptibility genes (BRCA1 and BRCA2) in breast (MCF-7 and T47D) and prostate (DU-145 and LNCaP) cancer cell types, in a time- and dose-dependent fashion. Induction of the BRCA genes occurred at low doses of I3C (20 μM) and genistein (0.5–1.0 μM), suggesting potential relevance to cancer prevention. A combination of I3C and genistein gave greater than expected induction of BRCA expression. Studies using small interfering RNAs (siRNAs) and BRCA expression vectors suggest that the phytochemical induction of BRCA2 is due, in part, to BRCA1. Functional studies suggest that I3C-mediated cytoxicity is, in part, dependent upon BRCA1 and BRCA2. Inhibition of E2-stimulated ER-α activity by I3C and genistein was dependent upon BRCA1; and inhibition of ligand-inducible androgen receptor (AR) activity by I3C and genistein was partially reversed by BRCA1-siRNA. Finally, we provide evidence suggesting that the phytochemical induction of BRCA1 expression is due, in part, to endoplasmic reticulum stress response signalling. These findings suggest that the BRCA genes are molecular targets for some of the activities of I3C and genistein

Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS). prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients