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Background Understanding the genetic basis of adaptive evolution is one of the major goals in evolutionary biology. Recently, it has been revealed that gene copy number variations (GCNVs) constitute significant proportions of genomic diversities within natural populations. However, it has been unclear whether GCNVs are under positive selection and contribute to adaptive evolution. Parallel evolution refers to adaptive evolution of the same trait in related but independent lineages, and three-spined stickleback (Gasterosteus aculeatus) is a well-known model organism. Through identification of genetic variations under parallel selection, i.e., variations shared among related but independent lineages, evidence of positive selection is obtained. In this study, we investigated whole-genome resequencing data from the marine and freshwater groups of three-spined sticklebacks from diverse areas along the Pacific and Atlantic Ocean coastlines, and searched for GCNVs under parallel selection. Results We identified 24 GCNVs that showed significant differences in the numbers of mapped reads between the two groups, and this number was significantly larger than that expected by chance. The derived group, i.e., freshwater group, was typically characterized by larger gene-copy numbers, which implied that gene duplications or multiplications helped with adaptation to the freshwater environment. Some of the identified GCNVs were those of multigenic family genes, which is consistent with the theory that fatal effects due to copy-number changes of multigenic family genes tend to be less than those of single-copy genes. Conclusion The identification of GCNVs that were likely under parallel selection suggests that contribution of GCNVs should be considered in studies on adaptive evolution. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-735) contains supplementary material, which is available to authorized users.

Background Teleost intestine is crucial for seawater acclimation by sensing osmolality of imbibed seawater and regulating drinking and water/ion absorption. Regulatory genes for transforming intestinal function have not been identified. A transcriptomic approach was used to search for such genes in the intestine of euryhaline medaka. Results Quantitative RNA-seq by Illumina Hi-Seq Sequencing method was performed to analyze intestinal gene expression 0 h, 1 h, 3 h, 1 d, and 7 d after seawater transfer. Gene ontology (GO) enrichment results showed that cell adhesion, signal transduction, and protein phosphorylation gene categories were augmented soon after transfer, indicating a rapid reorganization of cellular components and functions. Among >50 transiently up-regulated transcription factors selected via co-expression correlation and GO selection, five transcription factors, including CEBPB and CEBPD, were confirmed by quantitative PCR to be specific to hyperosmotic stress, while others were also up-regulated after freshwater control transfer, including some well-known osmotic-stress transcription factors such as SGK1 and TSC22D3/Ostf1. Protein interaction networks suggest a high degree of overlapping among the signaling of transcription factors that respond to osmotic and general stresses, which sheds light on the interpretation of their roles during hyperosmotic stress and emergency. Conclusions Since cortisol is an important hormone for seawater acclimation as well as for general stress in teleosts, emergency and osmotic challenges could have been evolved in parallel and resulted in the overlapped signaling networks. Our results revealed important interactions among transcription factors and offer a multifactorial perspective of genes involved in seawater acclimation. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-1134) contains supplementary material, which is available to authorized users.

RNA-binding proteins (RBPs) bind to their target RNA molecules by recognizing specific RNA sequences and structural contexts. The development of CLIP-seq and related protocols has made it possible to exhaustively identify RNA fragments that bind to RBPs. However, no efficient bioinformatics method exists to reveal the structural specificities of RBP–RNA interactions using these data. We present CapR, an efficient algorithm that calculates the probability that each RNA base position is located within each secondary structural context. Using CapR, we demonstrate that several RBPs bind to their target RNA molecules under specific structural contexts. CapR is available at https://sites.google.com/site/fukunagatsu/software/capr.

Uncertainties surrounding the evolutionary origin of the epipelagic fish family Scombridae (tunas and mackerels) are symptomatic of the difficulties in resolving suprafamilial relationships within Percomorpha, a hyperdiverse teleost radiation that contains approximately 17,000 species placed in 13 ill-defined orders and 269 families. Here we find that scombrids share a common ancestry with 14 families based on (i) bioinformatic analyses using partial mitochondrial and nuclear gene sequences from all percomorphs deposited in GenBank (10,733 sequences) and (ii) subsequent mitogenomic analysis based on 57 species from those targeted 15 families and 67 outgroup taxa. Morphological heterogeneity among these 15 families is so extraordinary that they have been placed in six different perciform suborders. However, members of the 15 families are either coastal or oceanic pelagic in their ecology with diverse modes of life, suggesting that they represent a previously undetected adaptive radiation in the pelagic realm. Time-calibrated phylogenies imply that scombrids originated from a deep-ocean ancestor and began to radiate after the end-Cretaceous when large predatory epipelagic fishes were selective victims of the Cretaceous-Paleogene mass extinction. We name this clade of open-ocean fishes containing Scombridae “Pelagia” in reference to the common habitat preference that links the 15 families.

In the trial and research phases, the fabrication of micro electro mechanical systems (MEMS) devices and integrated circuits (ICs) is both lengthy and costly, owing to the demands imposed by the use of photomasks. Maskless lithography techniques, such as electron beam (EB), laser scanning, and digital mirror device (DMD) lithography techniques, are widely used. In the MEMS field, submicron and wiring patterns are often created on uneven structures. We have developed a maskless lithography technique by modifying a DMD with two automatically switchable lenses. The first lens with a magnification power of 10× and a numerical aperture (NA) of 0.3 was used to rapidly expose wide areas, and the second lens with a magnification power of 100× and an NA of 0.9 was used for fine patterning. In the present study, we fabricated submicron patterns, wiring patterns, and alignment marks on slanted and deeply etched surfaces, and three-dimensional photoresist structures using our developed DMD lithography technique.

Nd3+ complex doped polymer liquid laser have been demonstrated and the threshold of the laser was also calculated. The calculation results that a laser media with 2 mm length is suitable for low threshold laser oscillation. We obtained the slope efficiency of 20% and the maximum output energy of 5.3 mJ at the pumping energy of 31 mJ by the method of the side pumping. To the best of knowledge, this is the highest slope efficiency of the bulky laser using Nd3+ complex.

In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which representmany fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics., 35 pages. This is a corrected version of the published paper: PLoS ONE 6(2):e16450, 2011. The original version is available from http://www.plosone.org/article/info:doi/10.1371/journal.pone.0016450

Background With rapid advances in genome sequencing and editing technologies, systematic and quantitative analysis of animal behavior is expected to be another key to facilitating data-driven behavioral genetics. The nematode Caenorhabditis elegans is a model organism in this field. Several video-tracking systems are available for automatically recording behavioral data for the nematode, but computational methods for analyzing these data are still under development. Results In this study, we applied the Gaussian mixture model-based binning method to time-series postural data for 322 C. elegans strains. We revealed that the occurrence patterns of the postural states and the transition patterns among these states have a relationship as expected, and such a relationship must be taken into account to identify strains with atypical behaviors that are different from those of wild type. Based on this observation, we identified several strains that exhibit atypical transition patterns that cannot be fully explained by their occurrence patterns of postural states. Surprisingly, we found that two simple factors—overall acceleration of postural movement and elimination of inactivity periods—explained the behavioral characteristics of strains with very atypical transition patterns; therefore, computational analysis of animal behavior must be accompanied by evaluation of the effects of these simple factors. Finally, we found that the npr-1 and npr-3 mutants have similar behavioral patterns that were not predictable by sequence homology, proving that our data-driven approach can reveal the functions of genes that have not yet been characterized. Conclusion We propose that elimination of inactivity periods and overall acceleration of postural change speed can explain behavioral phenotypes of strains with very atypical postural transition patterns. Our methods and results constitute guidelines for effectively finding strains that show “truly” interesting behaviors and systematically uncovering novel gene functions by bioimage-informatic approaches. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1408-8) contains supplementary material, which is available to authorized users.

In this study, we developed a micropyramid array electrode that facilitates contact between a nitrocellulose membrane and electrode, which is important to realize a quantitative and sensitive electrochemical detection system for immunochromatography. We evaluated the micropyamid array electrode with our newly developed detection system that can measure contact forces between a membrane and electrode, and also investigated the relationship between redox current and contact forces. By using normal pulse voltammetry, we observed higher reduction currents over a flat surface electrode at lower contact forces with the micropyramid array.

The overwhelming amount of network data in functional genomics is making its visualization cluttered with jumbling nodes and edges. Such cluttered network visualization, which is known as "hair-balls", is significantly hindering data interpretation and analysis of researchers. Effective navigation approaches that can always abstract network data properly and present them insightfully are hence required, to help researchers interpret the data and acquire knowledge efficiently. Cytoscape is a de facto standard platform for network visualization and analysis, which has many users around the world. Apart from its core sophisticated features, it easily allows for extension of the functionalities by loading extra plug-ins. We developed NaviClusterCS, which enables researchers to interactively navigate large biological networks of ~100,000 nodes in a "Google Maps-like" manner in the Cytoscape environment. NaviClusterCS rapidly and automatically identifies biologically meaningful clusters in large networks, e.g., proteins sharing similar biological functions in protein-protein interaction networks. Then, it displays not all nodes but only preferable numbers of those clusters at any magnification to avoid creating the cluttered network visualization, while its zooming and re-centering functions still enable researchers to interactively analyze the networks in detail. Its application to a real Arabidopsis co-expression network dataset illustrated a practical use of the tool for suggesting knowledge that is hidden in large biological networks and difficult to be obtained using other visualization methods. NaviClusterCS provides interactive and multi-scale network navigation to a wide range of biologists in the big data era, via the de facto standard platform for network visualization. It can be freely downloaded at http://navicluster.cb.k.u-tokyo.ac.jp/cs/ and installed as a plug-in of Cytoscape.