This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.

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The whole-genome sequence of an epidemic, multidrug-resistant Acinetobacter baumannii strain (strain ACICU) belonging to the European clone II group and carrying the plasmid-mediated bla OXA-58 carbapenem resistance gene was determined. The A. baumannii ACICU genome was compared with the genomes of A. baumannii ATCC 17978 and Acinetobacter baylyi ADP1, with the aim of identifying novel genes related to virulence and drug resistance. A. baumannii ACICU has a single chromosome of 3,904,116 bp (which is predicted to contain 3,758 genes) and two plasmids, pACICU1 and pACICU2, of 28,279 and 64,366 bp, respectively. Genome comparison showed 86.4% synteny with A. baumannii ATCC 17978 and 14.8% synteny with A. baylyi ADP1. A conspicuous number of transporters belonging to different superfamilies was predicted for A. baumannii ACICU. The relative number of transporters was much higher in ACICU than in ATCC 17978 and ADP1 (76.2, 57.2, and 62.5 transporters per Mb of genome, respectively). An antibiotic resistance island, AbaR2, was identified in ACICU and had plausibly evolved by reductive evolution from the AbaR1 island previously described in multiresistant strain A. baumannii AYE. Moreover, 36 putative alien islands (pAs) were detected in the ACICU genome; 24 of these had previously been described in the ATCC 17978 genome, 4 are proposed here for the first time and are present in both ATCC 17978 and ACICU, and 8 are unique to the ACICU genome. Fifteen of the pAs in the ACICU genome encode genes related to drug resistance, including membrane transporters and ex novo acquired resistance genes. These findings provide novel insight into the genetic basis of A. baumannii resistance.

Key Points• UDS demonstrated that BCR-ABL KD mutations detectable with conventional methods may just be the tip of the iceberg.• The information provided by conventional Sanger sequencing may not always be sufficient to predict responsiveness to a given TKI.In chronic myeloid leukemia and Philadelphia chromosome-positive acute lymphoblastic leukemia, tyrosine kinase inhibitor (TKI) therapy may select for drug-resistant BCR-ABL mutants. We used an ultra-deep sequencing (UDS) approach to resolve qualitatively and quantitatively the complexity of mutated populations surviving TKIs and to investigate their clonal structure and evolution over time in relation to therapeutic intervention. To this purpose, we performed a longitudinal analysis of 106 samples from 33 patients who had received sequential treatment with multiple TKIs and had experienced sequential relapses accompanied by selection of 1 or more TKI-resistant mutations. We found that conventional Sanger sequencing had misclassified or underestimated BCR-ABL mutation status in 55% of the samples, where mutations with 1% to 15% abundance were detected. A complex clonal texture was uncovered by clonal analysis of samples harboring multiple mutations and up to 13 different mutated populations were identified. The landscape of these mutated populations was found to be highly dynamic. The high degree of complexity uncovered by UDS indicates that conventional Sanger sequencing might be an inadequate tool to assess BCR-ABL kinase domain mutation status, which currently represents an important component of the therapeutic decision algorithms. Further evaluation of the clinical usefulness of UDS-based approaches is warranted. (Blood. 2013;122(9):1634-1648

Background: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A) + transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts.