Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

<p>Abstract</p> <p>Background</p> <p>Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs). Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized.</p> <p>Results</p> <p>We took a different approach from a straightforward extension of the Sankoff algorithm to the multiple alignments from the viewpoints of accuracy and time complexity. As a new option of the MAFFT alignment program, we developed a multiple RNA alignment framework, X-INS-i, which builds a multiple alignment with an iterative method incorporating structural information through two components: (1) pairwise structural alignments by an external pairwise alignment method such as SCARNA or LaRA and (2) a new objective function, Four-way Consistency, derived from the base-pairing probability of every sub-aligned group at every multiple alignment stage.</p> <p>Conclusion</p> <p>The BRAliBASE benchmark showed that X-INS-i outperforms other methods currently available in the sum-of-pairs score (SPS) criterion. As a basis for predicting common secondary structure, the accuracy of the present method is comparable to or rather higher than those of the current leading methods such as RNA Sampler. The X-INS-i framework can be used for building a multiple RNA alignment from any combination of algorithms for pairwise RNA alignment and base-pairing probability. The source code is available at the webpage found in the Availability and requirements section.</p

Rapid and Sensitive Detection of Breast Cancer Cells in Patient Blood with Nuclease-Activated Probe Technology

A challenge for circulating tumor cell (CTC)-based diagnostics is the development of simple and inexpensive methods that reliably detect the diverse cells that make up CTCs. CTC-derived nucleases are one category of proteins that could be exploited to meet this challenge. Advantages of nucleases as CTC biomarkers include: (1) their elevated expression in many cancer cells, including cells implicated in metastasis that have undergone epithelial-to-mesenchymal transition; and (2) their enzymatic activity, which can be exploited for signal amplification in detection methods. Here, we describe a diagnostic assay based on quenched fluorescent nucleic acid probes that detect breast cancer CTCs via their nuclease activity. This assay exhibited robust performance in distinguishing breast cancer patients from healthy controls, and it is rapid, inexpensive, and easy to implement in most clinical labs. Given its broad applicability, this technology has the potential to have a substantive impact on the diagnosis and treatment of many cancers. Keywords: cancer, circulating tumor cells, diagnostic nucleic acids, nucleases, diagnostic markers, breast cancer, liquid biops

Progressive multiple sequence alignments from triplets

<p>Abstract</p> <p>Background</p> <p>The quality of progressive sequence alignments strongly depends on the accuracy of the individual pairwise alignment steps since gaps that are introduced at one step cannot be removed at later aggregation steps. Adjacent insertions and deletions necessarily appear in arbitrary order in pairwise alignments and hence form an unavoidable source of errors.</p> <p>Research</p> <p>Here we present a modified variant of progressive sequence alignments that addresses both issues. Instead of pairwise alignments we use exact dynamic programming to align sequence or profile triples. This avoids a large fractions of the ambiguities arising in pairwise alignments. In the subsequent aggregation steps we follow the logic of the Neighbor-Net algorithm, which constructs a phylogenetic network by step-wisely replacing triples by pairs instead of combining pairs to singletons. To this end the three-way alignments are subdivided into two partial alignments, at which stage all-gap columns are naturally removed. This alleviates the "once a gap, always a gap" problem of progressive alignment procedures.</p> <p>Conclusion</p> <p>The three-way Neighbor-Net based alignment program aln3nn is shown to compare favorably on both protein sequences and nucleic acids sequences to other progressive alignment tools. In the latter case one easily can include scoring terms that consider secondary structure features. Overall, the quality of resulting alignments in general exceeds that of clustalw or other multiple alignments tools even though our software does not included heuristics for context dependent (mis)match scores.</p