The fly Drosophila melanogaster is one of the most intensively studied organisms in biology and serves as a model system for the investigation of many developmental and cellular processes common to higher eukaryotes, including humans. We have determined the nucleotide sequence of nearly all of the ∼120-megabase euchromatic portion of the Drosophila genome using a whole-genome shotgun sequencing strategy supported by extensive clone-based sequence and a high-quality bacterial artificial chromosome physical map. Efforts are under way to close the remaining gaps; however, the sequence is of sufficient accuracy and contiguity to be declared substantially complete and to support an initial analysis of genome structure and preliminary gene annotation and interpretation. The genome encodes ∼13,600 genes, somewhat fewer than the smaller Caenorhabditis elegans genome, but with comparable functional diversity.

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing. A computational method, RESCUE-ESE, was developed that predicts which sequences have ESE activity by statistical analysis of exon-intron and splice site composition. When large data sets of human gene sequences were used, this method identified 10 predicted ESE motifs. Representatives of all 10 motifs were found to display enhancer activity in vivo, whereas point mutants of these sequences exhibited sharply reduced activity. The motifs identified enable prediction of the splicing phenotypes of exonic mutations in human genes.

BackgroundEvaluation of cancer biomarkers from blood could significantly enable biomarker assessment by providing a relatively non-invasive source of representative tumor material. Circulating Tumor Cells (CTCs) isolated from blood of metastatic cancer patients hold significant promise in this regard.Methodology/Principal FindingsUsing spiked tumor-cells we evaluated CTC capture on different CTC technology platforms, including CellSearch® and two biochip platforms, and used the isolated CTCs to develop and optimize assays for molecular characterization of CTCs. We report similar performance for the various platforms tested in capturing CTCs, and find that capture efficiency is dependent on the level of EpCAM expression. We demonstrate that captured CTCs are amenable to biomarker analyses such as HER2 status, qRT-PCR for breast cancer subtype markers, KRAS mutation detection, and EGFR staining by immunofluorescence (IF). We quantify cell surface expression of EGFR in metastatic lung cancer patient samples. In addition, we determined HER2 status by IF and FISH in CTCs from metastatic breast cancer patients. In the majority of patients (89%) we found concordance with HER2 status from patient tumor tissue, though in a subset of patients (11%), HER2 status in CTCs differed from that observed in the primary tumor. Surprisingly, we found CTC counts to be higher in ER+ patients in comparison to HER2+ and triple negative patients, which could be explained by low EpCAM expression and a more mesenchymal phenotype of tumors belonging to the basal-like molecular subtype of breast cancer.Conclusions/SignificanceOur data suggests that molecular characterization from captured CTCs is possible and can potentially provide real-time information on biomarker status. In this regard, CTCs hold significant promise as a source of tumor material to facilitate clinical biomarker evaluation. However, limitations exist from a purely EpCAM based capture system and addition of antibodies to mesenchymal markers could further improve CTC capture efficiency to enable routine biomarker analysis from CTCs.

The basal-like subtype of breast cancer has an aggressive clinical behavior compared to that of the luminal subtype. We identified the microRNAs (miRNAs) miR-221 and miR-222 (miR-221/222) as basal-like subtype-specific miRNAs and showed that expression of miR-221/222 decreased expression of epithelial-specific genes and increased expression of mesenchymal-specific genes, and increased cell migration and invasion in a manner characteristic of the epithelial-to-mesenchymal transition (EMT). The transcription factor FOSL1 (also known as Fra-1), which is found in basal-like breast cancers but not in the luminal subtype, stimulated the transcription of miR-221/222, and the abundance of these miRNAs decreased with inhibition of the epidermal growth factor receptor (EGFR) or MEK (mitogen-activated or extracellular signal-regulated protein kinase kinase), placing miR-221/222 downstream of the RAS pathway. Furthermore, miR-221/222-mediated reduction in E-cadherin abundance depended on their targeting the 3' untranslated region of the GATA family transcriptional repressor TRPS1 (tricho-rhino-phalangeal syndrome type 1), which inhibited EMT by decreasing ZEB2 (zinc finger E-box-binding homeobox2) expression. We conclude that by promoting EMT, miR-221/222 may contribute to the more aggressive clinical behavior of basal-like breast cancers.

With the human genome sequence approaching completion, a major challenge is to identify the locations and encoded protein sequences of all human genes. To address this problem we have developed a new gene identification algorithm, GenomeScan, which combines exon-intron and splice signal models with similarity to known protein sequences in an integrated model. Extensive testing shows that GenomeScan can accurately identify the exon-intron structures of genes in finished or draft human genome sequence with a low rate of false-positives. Application of GenomeScan to 2.7 billion bases of human genomic DNA identified at least 20,000-25,000 human genes out of an estimated 30,000-40,000 present in the genome. The results show an accurate and efficient automated approach for identifying genes in higher eukaryotic genomes and provide a first-level annotation of the draft human genome.

A typical gene contains two levels of information: a sequence that encodes a particular protein and a host of other signals that are necessary for the correct expression of the transcript. While much attention has been focused on the effects of sequence variation on the amino acid sequence, variations that disrupt gene processing signals can dramatically impact gene function. A variation that disrupts an exonic splicing enhancer (ESE), for example, could cause exon skipping which would result in the exclusion of an entire exon from the mRNA transcript. RESCUE-ESE, a computational approach used in conjunction with experimental validation, previously identified 238 candidate ESE hexamers in human genes. The RESCUE-ESE method has recently been implemented in three additional species: mouse, zebrafish and pufferfish. Here we describe an online ESE analysis tool (http://genes.mit.edu/burgelab/rescue-ese/) that annotates RESCUE-ESE hexamers in vertebrate exons and can be used to predict splicing phenotypes by identifying sequence changes that disrupt or alter predicted ESEs.

Background: Epigenetics is the study of heritable changes in gene function that cannot be explained by changes in DNA sequence. One of the most commonly studied epigenetic alterations is cytosine methylation, which is a well recognized mechanism of epigenetic gene silencing and often occurs at tumor suppressor gene loci in human cancer. Arrays are now being used to study DNA methylation at a large number of loci; for example, the Illumina GoldenGate platform assesses DNA methylation at 1505 loci associated with over 800 cancer-related genes. Model-based cluster analysis is often used to identify DNA methylation subgroups in data, but it is unclear how to cluster DNA methylation data from arrays in a scalable and reliable manner.

Preeclampsia (PE), which affects 4-8% of human pregnancies, causes significant maternal and neonatal morbidity and mortality. Within the basal plate, placental cytotrophoblasts (CTBs) of fetal origin invade the uterus and extensively remodel the maternal vasculature. In PE, CTB invasion is often shallow, and vascular remodeling is rudimentary. To better understand possible causes, we conducted a global analysis of gene expression at the maternal-fetal interface in placental samples from women with PE (n = 12; 24-36 wk) vs. samples from women who delivered due to preterm labor with no evidence of infection (n = 11; 24-36 wk), a condition that our previous work showed is associated with normal CTB invasion. Using the HG-U133A&B Affymetrix GeneChip platform, and statistical significance set at log odds-ratio of B >0, 55 genes were differentially expressed in PE. They encoded proteins previously associated with PE [e.g. Flt-1 (vascular endothelial growth factor receptor-1), leptin, CRH, and inhibin] and novel molecules [e.g. sialic acid binding Ig-like lectin 6 (Siglec-6), a potential leptin receptor, and pappalysin-2 (PAPP-A2), a protease that cleaves IGF-binding proteins]. We used quantitative PCR to validate the expression patterns of a subset of the genes. At the protein level, we confirmed PE-related changes in the expression of Siglec-6 and PAPP-A2, which localized to invasive CTBs and syncytiotrophoblasts. Notably, Siglec-6 placental expression is uniquely human, as is spontaneous PE. The functional significance of these novel observations may provide new insights into the pathogenesis of PE, and assaying the circulating levels of these proteins could have clinical utility for predicting and/or diagnosing PE.