rna interference ( rnai ) has opened new avenues for the systematic analysis of phenotypes . with the completion of many whole genome sequences
, rnai allows the depletion of gene products in a wide range of organisms , thus enabling reverse genetic approaches where genetic tools are lacking .
the molecular mechanism of rnai - mediated gene silencing is conserved from plants to higher animals and studies in many organisms have benefited tremendously from the availability of rnai libraries . compared to classical genetic screens , rnai has the advantage to provide a link from phenotype to gene without the need for positional cloning of mutant alleles , but it lacks the possibility to make stable mutations and may display non - specific off - target effects . depending on the experimental system ,
rnai approaches are amenable for high - throughput screening , thereby allowing complete genomes to be queried for specific phenotypes .
screens can be performed for whole organism phenotypes , which has been done in caenorhabditis elegans ( 1,2 ) .
cell - based rnai experiments have become widely used in particular in drosophila and to a smaller extent in vertebrates , organisms for which many cell lines are available ( 36 ) .
cell - based phenotypes can be measured using simple fluorescent or luminescence reporters or more complex phenotypes as can be detected by immunofluorescence and microscopy ( 7 ) .
however each phenotypic readout method has its specific analysis method and a generally accepted ontology for phenotypes is still missing . in the past few years different rnai libraries
have been constructed that cover large parts of many genomes . for invertebrates , such as c.elegans and drosophila ,
libraries can be produced relatively cheaply , since long double - stranded rnas ( dsrnas ) can be generated by in vitro transcription .
in addition , use of dsrna in these organisms does not elicit an interferon response ( 8,9 ) .
expression of dsrna in bacteria that are fed to c.elegans is sufficient to produce an efficient knock - down of target transcripts ( 9 ) . in drosophila cells ,
simple addition of long dsrna to the cell culture medium is sufficient for cells to take up the dsrnas and intracellularly dice them in many different 2123 bp sirnas ( 8) . the efficiency of rnai in invertebrates is likely due to the diversity of sirna species that are intracellularly produced .
drosophila cell - based assays are widely used since the genome is well - annotated and many cellular pathways are conserved from flies to man ( 10,11 ) .
for example , depleting dsh by rnai is sufficient to fully recapitulate a wg loss - of - function phenotype , whereas it is necessary to deplete all three homologs ( dvl13 ) in human cells to observe a wnt phenotype ( d. ingelfinger and m. boutros , unpublished data ) .
such examples occur in many cellular pathways and it might be necessary in mammalian cells to pool rnai reagents for multiple candidates to generate a loss - of - function phenotype . while this is technically possible , it will significantly increase the complexity of screens .
more than 20 genome - wide ( or genome - scale ) screens in drosophila cells have been published since 2003 and a key challenge remains to integrate and compare different datasets .
since many screens have been performed using different rnai libraries and readouts , a proper annotation using minimal information for rnai experiments would be required .
the equivalent of a miame convention is currently lacking and the breadth and quality of data provided for screens varies .
as large - scale studies remain largely untested in follow - up experiments for a certain period of time , it is crucial to systematically integrate phenotypes and annotation information to estimate false positive and false negative rates . a comparison across multiple screens
can also be used to evaluate the reliability of a phenotype or a particular rnai reagent used in these studies .
ultimately , phenotypic profiles of many screens can serve to cluster unknown genes and provide guideposts for follow - up analysis ( 12 ) .
since most cell - based rnai screens have been published using drosophila rnai libraries , these screens can serve as a model for the organization of data produced in large - scale rnai experiments . here
we describe a publicly accessible database to integrate annotation of rnai reagents and functional information obtained from large - scale rnai experiments .
the database allows the user to access phenotype data from published screens and the sequences of their underlying perturbation reagents .
specificity and other sequence features are displayed in the context of the genomic location of the targeted gene model .
genomernai also facilitates the design of new experiments , using previously designed rnai reagents from independent libraries and links to a design program of rnai constructs for independent retests ( 13 ) .
the database structure is flexible and allows adding large - scale cell - based phenotypic datasets from other organisms once they become available .
the database integrates the sequence information of the rnai reagents with phenotypic information based on genome - scale and genome - wide published rnai screens .
these include libraries used in heidelberg and boston ( 4,14 ) , by groups in san francisco and others ( 15 ) . using the sequence information ,
all rnai constructs were computationally mapped onto the latest genomic sequence using blast and mummer ( 16,17 ) and gene and isoform annotations were derived through the mapping process .
all probe information is visualized using an implementation of the generic genome browser ( gbrowse ) ( 18 ) .
additional information was added to describe the specificity of dsrnas . to this end , we have generated all possible 19mer sequences of annotated gene models ( in total > 40 mio . ) and identified homologous sequences in the complete genome .
these are annotated as  tracks in gbrowse and allow evaluation of the specificity of rnai probe sequences .
in addition , gbrowse tracks are included that show other types of non - specific regions , such as low complexity and repetitive elements in the gene model which should be avoided in the design of rnai probes .
phenotypes mapping to such elements should also be treated with caution until further confirmatory data is available .
furthermore , for every single 19mer sequence we have calculated an rnai efficiency score ( 19 ) which is shown as a 
the average predicted efficiency is shown for individual rnai probes from various libraries as well as a 
track for complete gene models in the gbrowse interface . specificity and efficiency information can also be used to guide the design of new rnai probes for follow - up experiments .
rnai phenotypes of large - scale screens from our own lab and all to - date published screens were curated from the author 's websites or the supplementary data . to date
, the database contains 24 genome - scale screens which were performed with different genome - wide and subset rnai libraries .
a total of 5436 phenotypes are currently stored in genomernai , which will be expanded as more data becomes available .
individual gene entries can be directly accessed via a linkout (  heidelberg rnai ) from flybase ( 20 ) . from the entry webpage of the database
, user can search by gene identifier , by rnai probe i d ( if known ) or by phenotype ( figure 1 ) . for all these search options more detailed web pages are available which offer advanced input options ( e.g. sequence homology search ) . through the  phenotype entry page a complete list of all phenotypes
this can then be used to access an individual gene or probe list . a second way to search for phenotypes and
probe menu page , the user can enter a drosophila ( or heterologous ) nucleotide or protein sequence which is mapped by using blast against the bdgp transcript file or probe files .
this allows for example to search for phenotypes of a homolog of human cdc2 or can be used to find all rnai probes from various libraries that overlap with a query sequence .
this page allows direct access to search function by gene , rnai i d or phenotype .
more detailed search pages which allow for example to search by sequence homology can be accessed via the main menu .
information with respect to genes or rnai probes is subsequently retrieved from the database . in case of gene query
, the database retrieves all mapped rnai probes and displays them as a table ( figure 2a ) , including information of phenotypes that were reported , the calculated target transcripts and whether all isoforms are targeted ( columns  transcripts and  specificity ) .
this view shows also how many in silico diced sirnas map to gene model and whether additional transcripts are targeted ( column  other targets ) by the dsrna .
the database allows then to drill down and retrieve more detailed information , including primer and amplicon sequences ( figure 2b ) by following the  rnai probe link as well as more detailed information on other targets by following the corresponding link .
the completeness of available rnai constructs in their genomic context is summarized in an interactive gbrowse implementation , which shows the gene model , the rnai probes of all available libraries and tracks that allow evaluating the efficiency and specificity of probe sequences ( figure 2c ) .
other gbrowse functions can then be used to extract for example non - targeted regions , common exons , regions with high specificity or regions of low - complexity .
( a ) the table shows the search results from a user query for all probes targeting the cg6210 transcripts .
specificity column summarizes how many of the theoretical possible diced 21mer sequences hit the transcript .
( b ) drill down to access sequence information associated with a particular rnai probe .
( c ) gbrowse image of all rnai probes that target a particular gene model .
if rnai probes target other genes in addition to the intended one , this information is displayed below the rnai probes [ e.g. fbgn0036141 ( cg6210 ) + 24 other targets ] .
an example of a database session is shown in figure 2 . in this case , the user searched for rnai probes that target cg6210 ( fbgn0036141 ) , a factor required for the secretion of wg / wnt ligands ( 3 ) .
figure 2a shows that multiple rnai probes are available in different libraries and also links to flybase , if more information on cg6210 is requested .
when the user selects the hfa10605 rnai probe , the database shows more detailed information , such as primer sequences used to amplify a template for in vitro transcription , the length and sequence of the amplicon .
this page also shows all other phenotypes that were observed with this rnai probe , allowing evaluation of the specificity of the rnai experiment .
when selecting the gbrowse image , the user can locate other rnai probes in relation to the gene model ; for example , whereas for cg6210 six dsrnas from different libraries have a similar location , a single dsrna (  amc - amplicon ) targets only one splice variant ( cg6210-ra ) and might give only a partial phenotype .
these assignments are even more complex for gene models that have a larger number of splice variants and/or overlapping transcripts .
the database can also be accessed through searching for phenotypes or selecting from an all phenotypes list which can be retrieved from phenotype search menu . through these pages , the database provides gene annotation by comparing phenotypes in the light of the sequence content of probes targeting the gene of interest .
furthermore , individual gene models are linked to external databases such as flybase and flight for other functional information .
a link to e - rnai ( 13 ) is provided to allow a direct redesign of independent rnai probes .
the genomernai database presents phenotype information of large - scale screens in the context of associated sequence information .
we believe that this is an important issue since in contrast to genetic mutants , rnai phenotypes depend on the specificity of the used sirnas or dsrnas ( 2123 ) .
furthermore , with changes in gene models , rnai phenotypes attributed to a specific gene may be linked to a different gene in the future .
rnai libraries evolve , as we learn more about the rnai mechanism and potential pitfalls such as off - target effects second generation libraries will incorporate these findings into design rules and attempt to generate more specific reagents and make them publicly available ( t. horn , a. kiger , m. boutros , unpublished data ) .
the genomernai database is linked to other databases , such as flight and flyrnai ( 24,25 ) .
while all these databases contain rnai phenotype information , the focus of genomernai is to present phenotypes in the context of genomic information , which should facilitate the analysis of rnai phenotypes with respect to gene models and specificity information .
genomernai has an integrated pipeline for mapping of rnai probes and phenotypes and integrating the information of different rnai libraries , but the focus is less on the integration of different genomic datasets as provided by flight .
a major issue in representing rnai phenotypes remains a lack of standards on minimal information which need to be provided for small and large - scale screening approaches , as well as an ontology to properly describe cellular phenotypes . with time
we expect that the community will develop such standards which will become a prerequisite for publication .
the same holds true for the analysis of numerical data associated with phenotypic information , which can be analyzed in different ways and which may lead to different 
phenotype lists depending on the arbitrary threshold that is being used as a cut - off .
compendia that include both primary data and the analysis route could alleviate analysis diversity and enable the re - analysis of datasets when new algorithms will be available or datasets will be cross - correlated ( 26,27 ) . in the future ,
we plan to add cell - based phenotypes from other species , such as human , including sequence information which is currently largely not available due to proprietary restrictions .
cross - specific comparisons should provide a useful means to extract functional and highly confirmed phenotypes .
 rna interference ( rnai ) has emerged as a powerful tool to generate loss - of - function phenotypes in a variety of organisms . combined with the sequence information of almost completely annotated genomes , 
 rnai technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome . as increasing large datasets of rnai - induced phenotypes become available , an important challenge remains the systematic integration and annotation of functional information . 
 genome - wide rnai screens have been performed both in caenorhabditis elegans and drosophila for a variety of phenotypes and several rnai libraries have become available to assess phenotypes for almost every gene in the genome . 
 these screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species . 
 the genomernai database provides access to published rnai phenotypes obtained from cell - based screens and maps them to their genomic locus , including possible non - specific regions . 
 the database also gives access to sequence information of rnai probes used in various screens . 
 it can be searched by phenotype , by gene , by rnai probe or by sequence and is accessible at 
INTRODUCTION
DATABASE CONTENT
DATA QUERY
DATA OUTPUT
CONCLUSIONS AND OUTLOOK
SUPPLEMENTARY DATA