polyglutamine ( polyq ) repeats are implicated in several neurodegenerative diseases , including huntington s disease and several spinocerebellar ataxia s .
it is commonly thought that a toxic gain - of - function mechanism is triggered by the presence of a polyq tract , involving a conformational change within the protein and the formation and deposition of -sheet rich amyloid - like fibrils ( 13 ) .
the length of the polyq repeat is critical to pathogenesis ; however , there is evidence that other protein factors , including the location , type and number of flanking domains can modulate pathogenesis ( 410 ) .
although there are many human polyq - containing proteins ( 11 ) , only nine polyq - containing proteins are implicated in pathogenesis , and the precise repeat threshold to pathogenesis varies within the disease subset , for example , a 37 glutamine repeat is sufficient to lead to huntington 's disease , while sca3 results only when the polyq repeat expands to 45 or greater ( 1214 ) .
many other human , non - disease related proteins contain polyq repeats , which are intrinsically prone to expansion at the genetic level ( 11,15,16 ) .
in fact , a 40 glutamine repeat is the normal allele present in forkhead box p2 transcription factor ; a protein that has not been found to be associated with a polyq disease ( 17,18 ) .
this evidence has led to the hypothesis that protein characteristics modulate the propensity of polyq - containing proteins to aggregate and cause disease . to investigate the variable characteristics of polyq proteins we have performed a bioinformatics investigation of the protein context of polyglutamine repeats , and constructed a web - accessible database of all human proteins containing a polyq repeat greater than seven glutamines in length , termed 
polyq. the polyq database provides a tool to compare the polyq repeat location , the occurrence / type of domains and the number of domain repeats present across disease and non - disease proteins .
polyq was created using open - source mysql relational database server software , version 5.0.82 ( http://www.mysql.com ) , running on an apple 8-core 3.0  ghz xeon / os x server ( version 10.5.8 ) .
a web - based query interface to the database was developed using the php5 programming language , hosted via apache 2.2.14 .
the user interface was developed with the utilisation of the jquery javascript library and jquery widgets .
the polyq database was populated by extracting all human sequences from the ncbi non - redundant ( nr ) database that contained at least seven consecutive glutamine residues .
we then performed a pfam ( 19 ) domain search to find protein domains within this subset of sequences .
the ncbi nr contains many versions of the same protein , which created bias in the statistical analysis of polyq location data .
we simplified the analysis by indentifying protein variants / isoforms and using only the longest protein isoforms ( which we termed 
multiple variants / isoforms of each protein were crudely identified by comparing the protein sequence following the polyq chains .
the original sequences were then subjected to the blastclust ( 20 ) , force ( 21 ) , mcl ( 22 ) and homoclust algorithms ( 23 ) , and the variants / isoforms were adjusted as necessary .
the crude identification used the 10 amino acids immediately after the polyq chain as a 
search string ; any sequence that had the 10 amino acids immediately following its own polyq chain was presumed to have homology with that sequence .
this yielded a total of 128 master sequences , from an original data set of > 700 polyq - containing human protein sequences .
the results of a typical search , shown in figure 1a , show both a graphical summary ( figure 1a , top ) and textual details ( figure 1a , bottom ) according to sequence classification ( see below ) .
the graphical summary shows pie chart and bar chart representations of the results according to sequence classification ( figure 1a , top ) , pfam domain occurrence ( figure 1b ) and pfam domain repetition ( figure 1c ) . retrieved database entries
are listed in table format with one row per protein , and three columns containing protein name ( with links to the genbank entry ) , pfam domains , and protein sequence ( with the polyq region annotated ) , respectively
. homologs in the database can be included or excluded from the search . from this view , the domain and sequence context of the polyq sequence can be identified and further interrogated . to aid analysis
figure 1.(a ) typical results of a simple search ( blank in this instance ) , showing graphical breakdown according to sequence classification ; results shown graphically according to domain occurrence ( b ) and domain repeats ( c ) using the tabs at top of page [ as seen in ( a ) ] . ( a ) typical results of a simple search ( blank in this instance ) , showing graphical breakdown according to sequence classification ; results shown graphically according to domain occurrence ( b ) and domain repeats ( c ) using the tabs at top of page [ as seen in ( a ) ] . the data are sorted and annotated according to the following sequence classifications : n - terminal polyqs
 sequences where the first polyq chain appears before all pfam domains ; c - terminal polyqs 
sequences where the polyq chains appear between the first pfam domain and the last pfam domain ; mid domain polyqs  sequences in which the polyq chain appears in the middle of a pfam domain , or overlaps a pfam domain ; no significant domain polyqs 
sequences that do not contain any significant pfam domains ; unclassified polyqs  sequences that did not fit into any of the above classifications .
each group is readily accessed using the tabs in the web page ( figure 1a ) .
we have also further reduced the redundancy in the data by clustering sequence homologs , and have also tagged known disease proteins .
the website features pre - constructed pages that show the database entries sorted according to non - disease and disease - causing proteins respectively .
this distinction is applied to the sequence classifications above , the domain occurrence ( e.g. listing all domains , figure 1b ) , and domain repeats ( figure 1c ) .
this allows database entries to be grouped and examined according to whether the polyq tracts are found in non - disease or disease - causing proteins ( figure 2 ) . 

figure 2.selecting the  stats menu text shows the entire database contents to be grouped into non - disease and disease causing proteins . to aid analysis
specific entries can be selected ( indicated by a tickbox ) , using the  examine button and grouped together . selecting
the  stats menu text shows the entire database contents to be grouped into non - disease and disease causing proteins . to aid analysis
the data are sorted and annotated according to the following sequence classifications : n - terminal polyqs 
sequences where the first polyq chain appears before all pfam domains ; c - terminal polyqs 
sequences where the last polyq chain appears after all pfam domains ; interdomain polyqs  sequences where the polyq chains appear between the first pfam domain and the last pfam domain ; mid domain polyqs  sequences in which the polyq chain appears in the middle of a pfam domain , or overlaps a pfam domain ; no significant domain polyqs 
sequences that do not contain any significant pfam domains ; unclassified polyqs  sequences that did not fit into any of the above classifications .
each group is readily accessed using the tabs in the web page ( figure 1a ) .
we have also further reduced the redundancy in the data by clustering sequence homologs , and have also tagged known disease proteins .
the website features pre - constructed pages that show the database entries sorted according to non - disease and disease - causing proteins respectively .
this distinction is applied to the sequence classifications above , the domain occurrence ( e.g. listing all domains , figure 1b ) , and domain repeats ( figure 1c ) .
this allows database entries to be grouped and examined according to whether the polyq tracts are found in non - disease or disease - causing proteins ( figure 2 ) . 

figure 2.selecting the  stats menu text shows the entire database contents to be grouped into non - disease and disease causing proteins . to aid analysis
examine button and grouped together . selecting the  stats menu text shows the entire database contents to be grouped into non - disease and disease causing proteins . to aid analysis
specific entries can be selected ( indicated by a tickbox ) , using the  examine button and grouped together .
polyq is a valuable resource for theoreticians and experimentalists looking for insights into the context of polyq repeats in proteins and relationships with disease .
although the query tool allows searching across much of the database , we are developing a custom interface that will allow user - configurable queries against the whole data set as well as user customization of how the results are displayed .
we are also adding the structural information [ e.g. from the scop ( 24 ) , cath ( 25 ) and pdb databases ( 26 ) ] to the resources such that the structural context of polyq repeats can be investigated .
this work is supported by national health and medical research council and the australian research council .
are nhmrc senior research fellows . funding for open access charge : national health and medical research council ( australia ) .
 the polyglutamine diseases are caused in part by a gain - of - function mechanism of neuronal toxicity involving protein conformational changes that result in the formation and deposition of -sheet rich aggregates . 
 recent evidence suggests that the misfolding mechanism is context - dependent , and that properties of the host protein , including the domain architecture and location of the repeat tract , can modulate aggregation . in order to allow the bioinformatic investigation of the context of polyglutamines , 
 we have constructed a database , polyq ( http://pxgrid.med.monash.edu.au/polyq ) . 
 we have collected the sequences of all human proteins containing runs of seven or more glutamine residues and annotated their sequences with domain information . 
 polyq can be interrogated such that the sequence context of polyglutamine repeats in disease and non - disease associated proteins can be investigated . 
INTRODUCTION
PolyQ DESCRIPTION AND USE
Sequence classification
Domain occurrence, repeats and disease statistics
CONCLUSIONS AND FUTURE DIRECTIONS
FUNDING