a quantitative trait locus ( qtl ) is a polymorphic locus containing alleles that differentially affect the expression of a specific phenotypic trait ( a genetic basis for physiological variation ) ( 1 ) .
the purpose of qtl research is to identify genes and gene variants that underlie these traits .
the association strength is reported as a linkage score . over the past 10 years qtl mapping
has resulted in identification of thousands of chromosomal regions containing genes predicted to be involved in many complex human diseases , such as diabetes , hypertension , obesity and many others ( 2 ) . despite the accelerated rate of qtl discovery in human and mammalian models , finding the genes that underlie quantitative traits
several large - scale efforts collect and organize mammalian qtl and linkage groups : mouse genome database ( mgd ) ( 4 ) , rat genome database ( rgd ) ( 5 ) , online mendelian inheritance in man ( 6 ) and entrez gene ( 7 ) . currently , qtl are not fully integrated with the different types of chromosomal maps .
for example , qtl mouse data are presented as genetic chromosomal positions while human linkage groups are reported as cytogenetic bands and rat qtl are positioned on radiation hybrid maps .
in addition , automated , high - throughput tools to map expressed sequences and genes to qtl are not available to date . here
we present a multi - species qtl database and analysis software named qtl matchmaker ( ) .
qtl matchmaker is a web - based application that processes data from multiple sources and provides a web site for the analysis of candidate genes in the context of genetic traits .
it accepts a list of genbank accession numbers and mrna refseq numbers for genes of interest .
qtl matchmaker then performs mapping of these genes against a curated qtl database and generates reports of co - localization events .
the qtl matchmaker database schema has been created in oracle database server , which is running on a linux platform .
the user interface is written in java programming language and communicates with the database through standard jdbc adapters . to provide for automated mapping of experimentally - derived candidate genes to qtl , we compiled human , mouse and rat qtl , as well as human linkage groups information from pubmed articles , mgd , entrez gene and rgd websites .
additional groups were collected from published reports on human linkage groups and qtl that were retrieved by text mining of pubmed abstracts with keywords : 
lod score. since mgd and rgd maintain a list of mouse and rat qtl references , we used this information to download the original publications and extract the information described below to populate the qtl matchmaker database .
qtl symbols , names , traits , flanking and peak markers associated with each qtl were collected from these publications along with lod scores , parental strains , type of cross or epidemiologic data in cases of human linkage analysis . for qtl annotation we adopted mammalian phenotype ontology ( 5 ) developed at mgd and rgd . to assign base pair and cytogenetic positions to all flanking and peak markers ,
we downloaded the ucsc genome browser ( 8)  sts and  cytoband positional tables and parsed them using the names of markers as keywords .
this step is automated and allows for periodic updates of the marker positions . to assign a search interval , qtl borders must be mapped experimentally via linkage crosses . however , a significant number of qtl are reported only by their peak markers . to address this gap we calculated the average qtl length in each species ( mouse , rat and human ) ( table 1 ) . in cases where qtl flanking markers are not known
, we assigned an interval by centering the average qtl length in the respective species on the qtl peak marker .
the intervals generated in this way are flagged to mark whether the qtl of interest has experimentally or statistically defined borders . to provide for cross - species comparison of qtl
rnblasttab positional tables which allow for finding predicted orthologs using an accession number of interest as query . as a result
the user can look directly at qtl that are positioned over a candidate gene in all three species automatically .
these tables are also updated with every new release of human , mouse and rat genome assemblies .
all this information is curated and maintained in a central database implemented on oracle server .
this allows researchers to upload new qtl to the database making it a dynamic , up - to - date tool . as a result
, qtl matchmaker provides the users with the most current and accurate information about genes and qtl co - localization events .
the qtl matchmaker home page allows the user to choose a species of interest among mouse , human and rat .
this choice dynamically leads to a second page where the traits of the chosen species are listed for further selection .
the user is asked to enter a genbank accession number or a mrna refseq number for the gene of interest .
we have downloaded the ucsc genome browser positional tables for human , mouse and rat known genes and expressed sequence tags to the qtl database . based on these tables each accession number
base pair position numbers of the transcript beginning ( 5 ) and ending ( 3 ) nucleotides are compared with the qtl base pair positions on the respective chromosome of the selected species .
if a gene is located within a qtl , information for the qtl is linked with the gene data . to enable parallel searches for more than one gene
this allows for high - throughput mapping of genes of interest and qtl . in instances where a gene maps to multiple qtl
the application generates a report file which presents the position of the genes and the qtl characteristics ( figure 1a ) . when analyzing this report file it is important to note that although a lot of genes can be in a qtl interval only a small percentage of those genes will be causal .
the results can be downloaded in a microsoft excel or html file format . from the qtl matchmaker home page
the user can also access the cross species search page and find predicted orthologs of the candidate gene .
orthologs are reported from the  mmblasttab ,  hgblasttab and  rnblasttab ucsc genome browser positional tables which contain the blastp results of known genes from the query and target species .
all orthologs are assigned start and end base pair chromosomal positions and matched with the qtl in the respective species .
the end report provides information on each qtl and the gene located inside it . as a result the user can identify qtl that are positioned over a gene of interest across all three species automatically ( figure 1b ) . to address the difficulties in resolving qtl architecture we prioritize qtl candidate genes by applying a genetical genomics approach ( 9 ) .
we currently use the qtl matchmaker for co - localizing transcripts culled from microarray experiments to physiologically related qtl in mouse , rat and human .
the comparative genomics application of this tool allows mapping of experimentally - defined genesets from transcriptome analysis of human diseases to related qtl in mouse and rat .
for example , we used the qtl matchmaker to map mouse and rat orthologs of a human geneset identified by microarray analysis of kidney biopsy material from patients with systemic lupus erythematosus ( 10 ) to autoimmune qtl in rodents .
another application which is currently being explored is the mapping of genes identified in mutagenesis screens to qtl . in cases
when a mutated gene shows a phenotype similar to the trait characterizing the qtl it co - localizes to , this gene becomes a high priority candidate for resolving the qtl genetic structure .
to provide for automated mapping of experimentally - derived candidate genes to qtl , we compiled human , mouse and rat qtl , as well as human linkage groups information from pubmed articles , mgd , entrez gene and rgd websites .
additional groups were collected from published reports on human linkage groups and qtl that were retrieved by text mining of pubmed abstracts with keywords : 
lod score. since mgd and rgd maintain a list of mouse and rat qtl references , we used this information to download the original publications and extract the information described below to populate the qtl matchmaker database .
qtl symbols , names , traits , flanking and peak markers associated with each qtl were collected from these publications along with lod scores , parental strains , type of cross or epidemiologic data in cases of human linkage analysis . for qtl annotation we adopted mammalian phenotype ontology ( 5 ) developed at mgd and rgd . to assign base pair and cytogenetic positions to all flanking and peak markers ,
we downloaded the ucsc genome browser ( 8)  sts and  cytoband positional tables and parsed them using the names of markers as keywords .
this step is automated and allows for periodic updates of the marker positions . to assign a search interval , qtl borders must be mapped experimentally via linkage crosses . however , a significant number of qtl are reported only by their peak markers . to address this gap we calculated the average qtl length in each species ( mouse , rat and human ) ( table 1 ) . in cases where qtl flanking markers are not known
, we assigned an interval by centering the average qtl length in the respective species on the qtl peak marker .
the intervals generated in this way are flagged to mark whether the qtl of interest has experimentally or statistically defined borders . to provide for cross - species comparison of qtl
rnblasttab positional tables which allow for finding predicted orthologs using an accession number of interest as query . as a result
the user can look directly at qtl that are positioned over a candidate gene in all three species automatically .
these tables are also updated with every new release of human , mouse and rat genome assemblies .
all this information is curated and maintained in a central database implemented on oracle server .
this allows researchers to upload new qtl to the database making it a dynamic , up - to - date tool . as a result
, qtl matchmaker provides the users with the most current and accurate information about genes and qtl co - localization events .
the qtl matchmaker home page allows the user to choose a species of interest among mouse , human and rat .
this choice dynamically leads to a second page where the traits of the chosen species are listed for further selection .
the user is asked to enter a genbank accession number or a mrna refseq number for the gene of interest .
we have downloaded the ucsc genome browser positional tables for human , mouse and rat known genes and expressed sequence tags to the qtl database . based on these tables each accession number
base pair position numbers of the transcript beginning ( 5 ) and ending ( 3 ) nucleotides are compared with the qtl base pair positions on the respective chromosome of the selected species .
if a gene is located within a qtl , information for the qtl is linked with the gene data . to enable parallel searches for more than one gene we have developed a batch query function of the qtl matchmaker .
this allows for high - throughput mapping of genes of interest and qtl . in instances where a gene maps to multiple qtl
the application generates a report file which presents the position of the genes and the qtl characteristics ( figure 1a ) . when analyzing this report file it is important to note that although a lot of genes can be in a qtl interval only a small percentage of those genes will be causal .
the results can be downloaded in a microsoft excel or html file format . from the qtl matchmaker home page
the user can also access the cross species search page and find predicted orthologs of the candidate gene .
orthologs are reported from the  mmblasttab ,  hgblasttab and  rnblasttab ucsc genome browser positional tables which contain the blastp results of known genes from the query and target species .
all orthologs are assigned start and end base pair chromosomal positions and matched with the qtl in the respective species .
the end report provides information on each qtl and the gene located inside it . as a result the user can identify qtl that are positioned over a gene of interest across all three species automatically ( figure 1b )
. to address the difficulties in resolving qtl architecture we prioritize qtl candidate genes by applying a genetical genomics approach ( 9 ) .
we currently use the qtl matchmaker for co - localizing transcripts culled from microarray experiments to physiologically related qtl in mouse , rat and human .
the comparative genomics application of this tool allows mapping of experimentally - defined genesets from transcriptome analysis of human diseases to related qtl in mouse and rat .
for example , we used the qtl matchmaker to map mouse and rat orthologs of a human geneset identified by microarray analysis of kidney biopsy material from patients with systemic lupus erythematosus ( 10 ) to autoimmune qtl in rodents .
another application which is currently being explored is the mapping of genes identified in mutagenesis screens to qtl . in cases
when a mutated gene shows a phenotype similar to the trait characterizing the qtl it co - localizes to , this gene becomes a high priority candidate for resolving the qtl genetic structure .
all the data within the qtl matchmaker database are freely available to the scientific community . in addition to the access through the user interface
this tool meets the challenge of large - scale genomic experiments providing genetic and ( patho)physiologic annotation of putative candidate genes for human diseases and prediction of their functions , biological associations and interactions . in an effort to generate cross - reference for experimentally - defined genes and the genetic basis of qtl in rodents and humans ,
this application integrates functional genomics data ( i.e. microarrays gene expression datasets and mutagenesis screen results ) with genetic and phenotype / disease traits association data . in summary ,
qtl matchmaker provides a platform for comparative genomics studies of qtl across human , mouse and rat species .
qtl matchmaker should be a useful resource to address the hitherto unmet need of linking gene expression and genetic determinants of complex traits and disease .
. it will continue to acquire qtl data through electronic data submission and data mining .
in addition , development of ontology annotation based on biomedical parts of ulms thesaurus and mesh trees would permit for keyword searches of the qtl database in the near future .
future improvements will also include graphical representation of the results as well as alignment of syntenic blocks containing qtl for identical traits across species to narrow qtl borders in silico .
qtl matchmaker query and input screenshots . ( a ) a section of a batch search output page .
 identifying genes that underlie quantitative trait loci ( qtl ) is a challenging task . here 
 , we present a new qtl software system , named qtl matchmaker . the system is designed to integrate and mine qtl information across human , mouse and rat genomes and to annotate functional genomic data . 
 it combines and organizes information from relevant public databases and publications and integrates qtl , physical , genetic and cytogenetic maps across human , mouse and rat . to make this application available to the research community 
 we have developed a website for high - throughput mapping of expressed sequences to qtl and for selection of candidate genes in the physiological genomics context of complex traits . 
 qtl matchmaker is accessible at 
INTRODUCTION
IMPLEMENTATION AND DATABASE STRUCTURE
Database design
Query and data retrieval
DATA AVAILABILITY
DISCUSSION
FUTURE DIRECTIONS
Figures and Tables