| First Author | Henderson ND | Year | 2004 |
| Journal | Behav Genet | Volume | 34 |
| Issue | 3 | Pages | 267-93 |
| PubMed ID | 14990867 | Mgi Jnum | J:88525 |
| Mgi Id | MGI:3033691 | Doi | 10.1023/B:BEGE.0000017872.25069.44 |
| Citation | Henderson ND, et al. (2004) QTL Analysis of Multiple Behavioral Measures of Anxiety in Mice. Behav Genet 34(3):267-93 |
| abstractText | In a test battery consisting of an open-field arena, a light-dark box, a mirror-chamber box, an elevated plus maze, and an elevated square maze, 1,671 mice were tested, generating over 100 putative measures of anxiety in rodents. Quantitative trait loci (QTL) analysis was carried out on all measures, plus composite measures and phenotypic factor scores. Significant LOD scores were found for QTL on 17 chromosomes, with large and consistent QTL behavioral effects on chromosomes 1, 4, 7, 8, 14, 15, l8, and X. QTL on chromosomes 4 and 8 largely influence locomotor activity in both home cages and novel environments, whereas QTL on chromosomes 1, 15, and 18 influence anxiety-related behaviors. Five genetically separable, cross-test dimensions of anxiety could be identified: (i) the suppression of locomotor activity in low to moderately anxiogenic regions of the tests; (ii) a shift toward proportionally less time and activity spent in high-anxiogenic test areas; (iii) the suppression of rearing behavior; (iv) increased latency to enter novel areas; (v) increased autonomic responses, as assessed by defecation and urination. Patterns of QTL influence on cross-test composite scores were distinctive. For example, the QTL on chromosome 1 strongly influenced safe-area locomotor activity (LOD = 35) and autonomic responses (LOD = 16), whereas the QTL on chromosome 15 influenced the proportion of activity in high-anxiogenic areas (LOD = 16), latency to enter novel areas (LOD = 36) and rearing behavior (LOD = 57). Phenotypic factor analysis identified factors heavily loaded on single tests, rather than cross-test factors. The use of factor analysis or within-test principal components for data reduction before genetic analysis was less satisfactory than using genetic dissection methods on the original measures and logically derived composites. |
