Details

Autor(en) / Beteiligte

• Rubin, Edward M
• Symula, Derek J
• Frazer, Kelly A
• Ueda, Yukihiko
• Denefle, Patrice
• Stevens, Mary E
• Wang, Zhi-En
• Locksley, Richard

Titel

Functional screening of an asthma QTL in YAC transgenic mice

Ist Teil von

• Nature genetics, 1999-10, Vol.23 (2), p.241-244

Ort / Verlag

London: Nature Publishing Group

Erscheinungsjahr

1999

Quelle

MEDLINE

Beschreibungen/Notizen

• Many quantitative trait loci (QTLs) contributing to genetically complex conditions have been discovered, but few causative genes have been identified. This is mainly due to the large size of QTLs and the subtle connection between genotype and quantitative phenotype associated with these conditions. Transgenic mice have been successfully used to analyse well-characterized genes suspected of contributing to quantitative traits. Although this approach is powerful for examining one gene at a time, it can be impractical for surveying the large genomic intervals containing many genes that are typically associated with QTLs. To screen for genes contributing to an asthma QTL mapped to human chromosome 5q3 (refs 6,7), we characterized a panel of large-insert 5q31 transgenics based on studies demonstrating that altering gene dosage frequently affects quantitative phenotypes normally influenced by that gene. This panel of human YAC transgenics, propagating a 1-Mb interval of chromosome 5q31 containing 6 cytokine genes and 17 partially characterized genes, was screened for quantitative changes in several asthma-associated phenotypes. Multiple independent transgenic lines with altered IgE response to antigen treatment shared a 180-kb region containing 5 genes, including those encoding human interleukin 4 (IL4) and interleukin 13 (IL13 ), which induce IgE class switching in B cells. Further analysis of these mice and mice transgenic for mouse Il4 and Il13 demonstrated that moderate changes in Il4 and Il13 expression affect asthma-associated phenotypes in vivo. This functional screen of large-insert transgenics enabled us to identify genes that influence the QTL phenotype in vivo.