• Introduction

• Search candidate genes for quantitative trait loci (QTL)

• Search candidate genes for diseases

• Search candidate genes for microarray experiments

• Example for searching candidate genes of QTL

• Example for searching candidate genes of disease loci

• Example for searching candidate genes of microarray experiments

Step1. Choose QTL module.

Step2. Specify species, chromosome and QTL region. Candidate gene search is now available for 16 species. QTL region can be specified through three ways: two flanking markers, base pairs or peak marker. Please note if the QTL covers a big part of the chromosome, there may be a significant delay while mapping phenotype to genotype.

Step3. Specify database and search strategy. On this page, you should see two search strategy areas, one is for OMIM, another is for PubMed. Each of search strategy area consists of three rows with one search box per row as shown below.

You can enter one or more search key words describing the specific phenotypic features into the search box. Words should be separated by spaces. Enclosing several words in quotation marks causes them to be evaluated as a phrase, such as "bone strength".

By default, words within a text box are combined with a Boolean OR unless otherwise specified by choosing from pull-down menu on the right of the search box.

You can restrict your search to a particular field using the pull-down menus on the left of the search box. The keyword search can be performed on full text, on title and abstract, or on title only for PubMed. In OMIM, it is available for full text, clinical synopsis field, or gene map disorder field.

To construct more complex queries, You can enter multiple words or phrases in the additional search boxes in each row and then select appropriate Boolean operators (AND, OR, NOT) using the pull-down menus on the left to connect the search terms in different search boxes.

For long strategies, click the plus sign at the top left of the search strategy area to add additional rows of search boxes. To remove search boxes, click the minus sign.

You can choose to perform search on PubMed only, OMIM only, or both by setting the check box at the top of the search strategy areas "checked" or "unchecked".

Step1. Choose disease locus module.

Step2. Specify species, chromosome and disease locus region. Candidate gene search is now available for 16 species. Disease locus can be specified through two ways: two flanking markers and base pairs. Please note if the disease locus covers a big part of the chromosome, there may be a significant delay while mapping phenotype to genotype.

Step3. Specify database and search strategy. On this page, you should see two search strategy areas, one is for OMIM, another is for PubMed. Each of search strategy area consists of three rows with one search box per row as shown below.

You can enter one or more search key words describing the specific phenotypic features into the search box. Words should be separated by spaces. Enclosing several words in quotation marks causes them to be evaluated as a phrase, such as "bone strength".

By default, words within a text box are combined with a Boolean OR unless otherwise specified by choosing from pull-down menu on the right of the search box.

You can restrict your search to a particular field using the pull-down menus on the left of the search box. The keyword search can be performed on full text, on title and abstract, or on title only for PubMed. In OMIM, it is available for full text, clinical synopsis field, or gene map disorder field.

To construct more complex queries, You can enter multiple words or phrases in the additional search boxes in each row and then select appropriate Boolean operators (AND, OR, NOT) using the pull-down menus on the left to connect the search terms in different search boxes.

For long strategies, click the plus sign at the top left of the search strategy area to add additional rows of search boxes. To remove search boxes, click the minus sign.

You can choose to perform search on PubMed only, OMIM only, or both by setting the check box at the top of the search strategy areas "checked" or "unchecked".

Step1. Choose microarray module.

Step2. Enter your gene list into text box or upload a plain text file containing one or more genes. Genes should be separated by spaces or newlines.

Step3. Specify database and search strategy. On this page, you should see two search strategy areas, one is for OMIM, another is for PubMed. Each of search strategy area consists of three rows with one search box per row as shown below.

You can enter one or more search key words describing the specific phenotypic features into the search box. Words should be separated by spaces. Enclosing several words in quotation marks causes them to be evaluated as a phrase, such as "bone strength".

By default, words within a text box are combined with a Boolean OR unless otherwise specified by choosing from pull-down menu on the right of the search box.

You can restrict your search to a particular field using the pull-down menus on the left of the search box. The keyword search can be performed on full text, on title and abstract, or on title only for PubMed. In OMIM, it is available for full text, clinical synopsis field, or gene map disorder field.

To construct more complex queries, You can enter multiple words or phrases in the additional search boxes in each row and then select appropriate Boolean operators (AND, OR, NOT) using the pull-down menus on the left to connect the search terms in different search boxes.

For long strategies, click the plus sign at the top left of the search strategy area to add additional rows of search boxes. To remove search boxes, click the minus sign.

You can choose to perform search on PubMed only, OMIM only, or both by setting the check box at the top of the search strategy areas "checked" or "unchecked".

Information of arthritis QTL

Rat QTL: Ciaa1 (Olofsson P, Lu S, Holmberg J, Song T, Wernhoff P, Pettersson U, Holmdahl R. A comparative genetic analysis between collagen-induced arthritis and pristane-induced arthritis. Arthritis Rheum 2003; 48(8):2332-2342)
Markers flanking the QTL: D20Mgh4(centromere)-D20Rat5
Note: D20Mgh4 is not mapped to the assembly in the current Ensembl database. We chose centromere for Ensembl searching as this marker is near centromere.
Search region: 1-28411969 (bp)
Key words describing QTL phenotype: arthritis
Causative genes: unknown

Step 1. Choose QTL Analysis.

Step2. Specify species, chromosome and QTL region. Candidate gene search is now available for 16 species. QTL region can be specified through three ways: two flanking markers, base pairs, or peak marker. Please note if the QTL covers a big part of the chromosome, there may be a significant delay while mapping phenotype to genotype.

Step3. Specify database and search strategy. On this page, complex search strategy can be easily constructed by using different combinations of key words or phrases, field qualifiers, text connectors, and Boolean operators. click here to learn more about how to construct complex search strategy.

Result page. On this page, You should see the search terms for OMIM and PubMed and three links. By default, links are blue with an underline. To view detailed information of genes, candidates and relevant literature reports, just click on the corresponding link.

QTL gene information page . this page provides you with detailed information of all genes within the QTL. By default, up to 30 items are displayed per page. You can click the buttons at top right to go to next page, previous page or save the results as Excel or PDF file.

OMIM candidate information page. this page provides you the detailed information of candidate genes from OMIM database. Candidates are sorted by the number of relevant references that can indicate its candidacy.

Clicking on the Ensembl accession number will link you to the gene report in Ensembl database.

For detailed reports in OMIM that can indicate the candidacy of a gene, just click on the link "view data" and then you will see a page like below..

Click on the accession number to view the specific report in OMIM database.

PubMed candidate information page. this page provides you the detailed information of candidate genes from PubMed database. Candidates are sorted by the number of relevant references that can indicate its candidacy.

Clicking on the Ensembl accession number will link you to the gene report in Ensembl database.

For detailed information of relevant references in PubMed that can indicate the candidacy of a gene, just click on the link "view data" and then you will see a page like below.

Click on the accession number to view the specific reference in PubMed database.

The information of mouse disease model.

Mouse model: lbab (http://www.jax.org/mmr/lbab.html)
Markers flanking disease locus: D1Mit9 (D1Mit46)-D1Mit488
Note: D1Mit9 is not mapped to the assembly in the current Ensembl database, alternatively, we chose a marker, D1Mit46 near D1Mit9 for Ensembl searching)
Key words describing disease phenotype: dwarfism, dwarfing
Causative gene: Nppc
Note: Nppc has been confirmed as the causative gene underlying lbab model by our lab, please see Yan Jiao, Jian Yan, Feng Jiao, HongBin Yang, Leah Rae Donahue, Xinmin Li, Bruce A. Roe, John Stuart, Weikuan Gu. A single nucleotide mutation in Nppc is associated with a long bone abnormality in lbab mice. BMC Genet. 2007 Apr 17;8(1):16

Step1. Choose Disease Locus Analysis..

Step2. Specify species, chromosome and disease locus region. Candidate gene search is now available for 16 species. disease locus region can be specified through two ways: two flanking markers or base pairs. Please note if the disease locus covers a big part of the chromosome, there may be a significant delay while mapping phenotype to genotype.

Step3. Specify database and search strategy. On this page, complex search strategy can be easily constructed by using different combinations of key words or phrases, field qualifiers, text connectors, and Boolean operators. click here to learn more about how to construct complex search strategy.

Result page. On this page, You should see the search terms for OMIM and PubMed and three links. By default, links are blue with an underline. To view detailed information of genes, candidates and relevant literature reports, just click on the corresponding link.

Disease locus gene information page . this page provides you with detailed information of all genes within disease locus. By default, up to 30 items are displayed per page. You can click the buttons at top right to go to next page, previous page or save the results as Excel or PDF file.

OMIM candidate information page. this page provides you the detailed information of candidate genes from OMIM database. Candidates are sorted by the number of relevant references that can indicate its candidacy.

Clicking on the Ensembl accession number will link you to the gene report in Ensembl database.

For detailed reports in OMIM that can indicate the candidacy of a gene, just click on the link "view data" and then you will see a page like below.

Click on the accession number to view the specific report in OMIM database.

PubMed candidate information page. this page provides you the detailed information of candidate genes from PubMed database. Candidates are sorted by the number of relevant references that can indicate its candidacy.

For detailed information of relevant references in PubMed that can indicate the candidacy of a gene, just click on the link "view data" and then you will see a page like below.

Click on the accession number to view the specific reference in PubMed database.

Information of microarray experiment

Experiment description: Chondrocytes from an osteoarthritis (OA) patient which were incubated without and with TGF beta for 24 hrs.
Microarry data: view data
Set of differentially expressed genes with two-fold change or more: view data
Note: we filtered duplicates and those genes without name.
Selected key words: TGFB1, TGFB, TGF-BETA, TGF BETA, arthritis, inflammation anti-inflammatory, inflammatory mediator, inflammatory cytokine, autoimmune

Step1. Choose Microarray Analysis.

Step2. Enter the genes of interest into the text area, or upload a plain text file containing one or more genes. Genes should be separated by spaces or newlines.

Step3. Specify database and search strategy. On this page, complex search strategy can be easily constructed by using different combinations of key words or phrases, field qualifiers, text connectors, and Boolean operators. click here to learn more about how to construct complex search strategy.

Result page. On this page, You should see the search terms for OMIM and PubMed and two links. By default, links are blue with an underline. To view detailed information of candidates and relevant literature reports, just click on the corresponding link.

OMIM candidate information page. this page provides you the detailed information of candidate genes from OMIM database. Candidates are sorted by the number of relevant references that can indicate its candidacy. By default, up to 30 items are displayed per page. You can click the buttons at top right to go to next page, previous page or save the results as Excel or PDF file.

For detailed reports in OMIM that can indicate the candidacy of a gene, just click on the link "view data" and then you will see a page like below.

Click on the accession number to view the specific report in OMIM database.

PubMed candidate information page. this page provides you the detailed information of candidate genes from PubMed database. Candidates are sorted by the number of relevant references that can indicate its candidacy.

For detailed information of relevant references in PubMed that can indicate the candidacy of a gene, just click on the link "view data" and then you will see a page like below.

Click on the accession number to view the specific reference in PubMed database.