To facilitate large-scale functional studies in Drosophila, the Drosophila Transgenic RNAi Project (TRiP) at Harvard Medical School (HMS) was established along with several goals: developing efficient vectors for RNAi that work in all tissues, generating a genome-scale collection of RNAi stocks with input from the community, distributing the lines as they are generated through existing stock centers, validating as many lines as possible using RT-qPCR and phenotypic analyses, and developing tools and web resources for identifying RNAi lines and retrieving existing information on their quality. With these goals in mind, here we describe in detail the various tools we developed and the status of the collection, which is currently composed of 11,491 lines and covering 71% of Drosophila genes. Data on the characterization of the lines either by RT-qPCR or phenotype is available on a dedicated website, the RNAi Stock Validation and Phenotypes Project (RSVP, http://www.flyrnai.org/RSVP.html), and stocks are available from three stock centers, the Bloomington Drosophila Stock Center (United States), National Institute of Genetics (Japan), and TsingHua Fly Center (China). KEYWORDS RNAi; Drosophila; screens; phenotypes; functional genomics A striking finding from the genomic revolution and wholegenome sequencing is the amount of information missing on gene function. Although Drosophila is arguably the bestunderstood multicellular organism and a proven model system for human diseases, mutations mapped to specific genes with readily detectable phenotypes have been isolated for 15% of the .13919 annotated fly coding genes (http:// flybase.org/; FlyBase R6.06). The lack of information on the majority of genes (the "phenotype gap") suggests that researchers have been unable to either assay their roles experimentally and/or resolve issues of functional redundancy. In addition, some phenotypes may be only detected on specific diets and environments. Further, our understanding of the function of many genes for which we have some information is limited by pleiotropy, whereby an earlier function of the gene prevents analysis of later functions.The availability of in vivo RNAi has revolutionized the ability of Drosophila researchers to disrupt the activity of single genes with spatial and temporal resolution (Dietzl et al. 2007; see review by Perrimon et al. 2010), and thus address the phenotype gap. Motivated by the power of the approach and the needs of the community, three large-scale efforts, the Vienna Drosophila RNAi Center (VDRC, http:// stockcenter.vdrc.at/control/main), the National Institute of Genetics (NIG, http://www.shigen.nig.ac.jp/fly/nigfly/index.jsp), and the Drosophila Transgenic RNAi Project (TRiP) at Harvard Medical School (HMS) (http://www.flyrnai.org/TRiP-HOME. html) have over the years generated large numbers of RNAi lines that aim to cover all Drosophila genes. These resources are proving invaluable to address a myriad of questions in various biological and biomedical fields including but not limite...

The reactions of aminoiminomethanesulfonic acid, phenylaminoiminomethanesulfonic acid, and N,N'-diphenylaminoiminomethanesulfonic acid in aqueous media at pH 7.4, 10, and 13-14 were investigated. At neutral pH hydrolysis to the corresponding urea was the major pathway for all three compounds. At higher pH phenylaminoiminomethanesulfonic acid reacted to give phenylcyanamide in nearly quantitative yield, while N,N'-diphenylaminoiminomethanesulfonic acid gave diphenylcarbodiimide which reacted further to give N,N'-diphenylurea. At pH 10 aminoiminomethanesulfonic acid reacted with itself, eventually giving N-cyanoguanidine, while at pH 13-14, elimination to cyanamide predominated. The reactions of glycine with the aminoiminomethanesulfonic acids gave guanylated acetic acids as products. The rates of these nucleophilic substitutions of the sulfonic acid group of the aminoiminomethanesulfonic acids by the amino group of glycine decreased in the order aminoiminomethanesulfonic acid greater than phenylaminoiminomethanesulfonic acid greater than (2-methylphenyl)aminoiminomethanesulfonic acid greater than (2,6-dimethylphenyl)aminoiminomethanesulfonic acid. Higher relative rates of substitution of the aminoiminomethanesulfonic acids appear to be related to higher relative toxicities for the corresponding thioureas.

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The ability to recognize mates, kin, offspring and neighbors by their individually distinctive traits-individual recognition (IR)-is widespread in animals. Much work has investigated IR from the perspective of the recognizer, but less is known about the extent to which signals have evolved to facilitate IR. To explore this, one approach is to compare putative identity signals among species that differ in life history and extent of IR. In Common Murres (Uria aalge), a colonially breeding seabird, the eggs of individual females are remarkably variable in terms of color and pattern (maculation).Common Murres also appear to recognize their own eggs, leading to the hypothesis that variable egg phenotypes evolved to promote recognizability. However, we lack a quantitative assessment of the egg pattern information in Common Murres and their close relatives. Here, we analyzed images of eggs laid by four alcid species: Common Murres, Thick-billed Murres (Uria lomvia), Razorbills (Alca torda) and Dovekies (Alle alle). We extracted pattern measures believed to be relevant to bird vision and calculated Beecher's information statistic (H s ), which allowed us to compare the amount of identity information contained in each species' egg patterns. Murres, which nest in dense colonies and can recognize their own eggs, have egg patterns with a relatively large amount of identity information compared to Razorbills and Dovekies. Egg recognition has not been demonstrated in Razorbills and Dovekies, whose colonies are less dense. Our results are consistent with the hypothesis that complex patterns of Murre eggs may have evolved to increase individual recognizability.

One contribution of 11 to a theme issue 'Living light: optics, ecology and design principles of natural photonic structures'.Subject Areas: environmental science, biomaterials, computational biology