Correction: The anti-tumorigenic activity of A2M-A lesson from the naked mole-rat.

[This corrects the article DOI: 10.1371/journal.pone.0189514.].

The anti-tumorigenic activity of A2M-A lesson from the naked mole-rat.

Cancer resistance is a major cause for longevity of the naked mole-rat. Recent liver transcriptome analysis in this animal compared to wild-derived mice revealed higher expression of alpha2-macroglobulin (A2M) and cell adhesion molecules, which contribute to the naked mole-rat's cancer resistance. Notably, A2M is known to dramatically decrease with age in humans. We hypothesize that this might facilitate tumour development. Here we found that A2M modulates tumour cell adhesion, migration and growth by inhibition of tumour promoting signalling pathways, e.g. PI3K / AKT, SMAD and up-regulated PTEN via down-regulation of miR-21, in vitro and in tumour xenografts. A2M increases the expression of CD29 and CD44 but did not evoke EMT. Transcriptome analysis of A2M-treated tumour cells, xenografts and mouse liver demonstrated a multifaceted regulation of tumour promoting signalling pathways indicating a less tumorigenic environment mediated by A2M. By virtue of these multiple actions the naturally occurring A2M has strong potential as a novel therapeutic agent.

Using a priori knowledge to align sequencing reads to their exact genomic position.

The use of a priori knowledge in the alignment of targeted sequencing data is investigated using computational experiments. Adapting a Needleman-Wunsch algorithm to incorporate the genomic position information from the targeted capture, we demonstrate that alignment can be done to just the target region of interest. When in addition use is made of direct string comparison, an improvement of up to a factor of 8 in alignment speed compared to the fastest conventional aligner (Bowtie) is obtained. This results in a total alignment time in targeted sequencing of around 7 min for aligning approximately 56 million captured reads. For conventional aligners such as Bowtie, BWA or MAQ, alignment to just the target region is not feasible as experiments show that this leads to an additional 88% SNP calls, the vast majority of which are false positives (≈ 92%).

mRNA-seq with agnostic splice site discovery for nervous system transcriptomics tested in chronic pain.

mRNA-seq is a paradigm-shifting technology because of its superior sensitivity and dynamic range and its potential to capture transcriptomes in an agnostic fashion, i.e., independently of existing genome annotations. Implementation of the agnostic approach, however, has not yet been fully achieved. In particular, agnostic mapping of pre-mRNA splice sites has not been demonstrated. The present study pursued dual goals: (1) to advance mRNA-seq bioinformatics toward unbiased transcriptome capture and (2) to demonstrate its potential for discovery in neuroscience by applying the approach to an in vivo model of neurological disease. We have performed mRNA-seq on the L4 dorsal root ganglion (DRG) of rats with chronic neuropathic pain induced by spinal nerve ligation (SNL) of the neighboring (L5) spinal nerve. We found that 12.4% of known genes were induced and 7% were suppressed in the dysfunctional (but anatomically intact) L4 DRG 2 wk after SNL. These alterations persisted chronically (2 mo). Using a read cluster classifier with strong test characteristics (ROC area 97%), we discovered 10,464 novel exons. A new algorithm for agnostic mapping of pre-mRNA splice junctions (SJs) achieved a precision of 97%. Integration of information from all mRNA-seq read classes including SJs led to genome reannotations specifically relevant for the species used (rat), the anatomical site studied (DRG), and the neurological disease considered (pain); for example, a 64-exon coreceptor for the nociceptive transmitter substance P was identified, and 21.9% of newly discovered exons were shown to be dysregulated. Thus, mRNA-seq with agnostic analysis methods appears to provide a highly productive approach for in vivo transcriptomics in the nervous system.