Excess of miRNA-378a-5p perturbs mitotic fidelity and correlates with breast cancer tumourigenesis <i>in vivo</i>

BACKGROUND: Optimal expression and proper function of key mitotic proteins facilitate control and repair processes that aim to prevent loss or gain of chromosomes, a hallmark of cancer. Altered expression of small regulatory microRNAs is associated with tumourigenesis and metastasis but the impact on mitotic signalling has remained unclear. METHODS: Cell-based high-throughput screen identified miR-378a-5p as a mitosis perturbing microRNA. Transient transfections, immunofluorescence, western blotting, time-lapse microscopy, FISH and reporter assays were used to characterise the mitotic anomalies by excess miR-378a-5p. Analysis of microRNA profiles in breast tumours was performed. RESULTS: Overexpression of miR-378a-5p induced numerical chromosome changes in cells and abrogated taxol-induced mitotic block via premature inactivation of the spindle assembly checkpoint. Moreover, excess miR-378a-5p triggered receptor tyrosine kinase–MAP kinase pathway signalling, and was associated with suppression of Aurora B kinase. In breast cancer in vivo, we found that high miR-378a-5p levels correlate with the most aggressive, poorly differentiated forms of cancer. INTERPRETATION: Downregulation of Aurora B by excess miR-378a-5p can explain the observed microtubule drug resistance and increased chromosomal imbalance in the microRNA-overexpressing cells. The results suggest that breast tumours may deploy high miR-378a-5p levels to gain growth advantage and antagonise taxane therapy

Scalable and Versatile k-mer Indexing for High-Throughput Sequencing Data

International audiencePhilippe et al. (2011) proposed a data structure called Gk ar- rays for indexing and querying large collections of high-throughput sequencing data in main-memory. The data structure supports versa- tile queries for counting, locating, and analysing the coverage profile of k-mers in short-read data. The main drawback of the Gk arrays is its space-consumption, which can easily reach tens of gigabytes of main- memory even for moderate size inputs. We propose a compressed variant of Gk arrays that supports the same set of queries, but in both near-optimal time and space. In practice, the compressed Gk arrays scale up to much larger inputs with highly competitive query times compared to its non-compressed predecessor. The main applica- tions include variant calling, error correction, coverage profiling, and sequence assembly