Identification and Profiling of MicroRNAs from Skeletal Muscle of the Common Carp

The common carp is one of the most important cultivated species in the world of freshwater aquaculture. The cultivation of this species is particularly productive due to its high skeletal muscle mass; however, the molecular mechanisms of skeletal muscle development in the common carp remain unknown. It has been shown that a class of non-coding ∼22 nucleotide RNAs called microRNAs (miRNAs) play important roles in vertebrate development. They regulate gene expression through sequence-specific interactions with the 3′ untranslated regions (UTRs) of target mRNAs and thereby cause translational repression or mRNA destabilization. Intriguingly, the role of miRNAs in the skeletal muscle development of the common carp remains unknown. In this study, a small-RNA cDNA library was constructed from the skeletal muscle of the common carp, and Solexa sequencing technology was used to perform high throughput sequencing of the library. Subsequent bioinformatics analysis identified 188 conserved miRNAs and 7 novel miRNAs in the carp skeletal muscle. The miRNA expression profiling showed that, miR-1, miR-133a-3p, and miR-206 were specifically expressed in muscle-containing organs, and that miR-1, miR-21, miR-26a, miR-27a, miR-133a-3p, miR-206, miR-214 and miR-222 were differentially expressed in the process of skeletal muscle development of the common carp. This study provides a first identification and profiling of miRNAs related to the muscle biology of the common carp. Their identification could provide clues leading towards a better understanding of the molecular mechanisms of carp skeletal muscle development

A Quadratically Convergent O(sqrt{n}L)-Iteration Algorithm for Linear Programming

Recently, Ye et al. proposed a large step modification of the Mizuno-Todd-Ye predictor-corrector interior-point algorithm for linear programming. They demonstrated that the large-step algorithm maintains theO (sqrt{n}L)-iteration complexity while exhibiting superlinear convergence of the duality gap to zero under the assumption that the iteration sequence converges, and quadratic convergence of the duality gap to zero under the assumption of nondegeneracy. In this paper we establish the quadratic convergence result without any assumption concerning the convergence of the iteration sequence or nondegeneracy. This surprising result, to our knowledge, is the first instance of polynomiality and superlinear (or quadratic) convergence for an interior-point algorithm which does not assume the convergence of the iteration sequence or nondegeneracy