1. Ping Wang, Mar-02-09 1 Method Paper

2. Ping Wang, Mar-02-09 2 Outline Methods –Multiple QTL model identification procedure –Adjacency Measurement –Clustering Methods QTL Archive Studies Application to F2 data: clinical trait data + expression data in islet

3. Ping Wang, Mar-02-09 3 Model Identification Procedure 1.Apply a single QTL mapping method. Pick several markers with relatively high LOD scores from each chromosome as candidate marker effects. 2.Identify baseline model, the best model with main effects only using stepwise regression and BIC (or pLOD) criterion. Allowed main effects are those cadidate marker effects identified in Step 1 and other covariates such as sex. 3.Identify the best model allowing first order interactions using stepwise regression, and BIC (or pLOD) criterion, starting from the baseline model. Allowed interactions are between main effects in the baseline model and all candidate marker effects.

4. Ping Wang, Mar-02-09 4 QTL archive studies (25 traits in 12 studies) TraitsBIC 1 (# main effects, # interactions)BIC 2 (# main effects, # interactions) Transformed % suppression-216.16(7,2)<-214.62(7,3) GBV-2242.01(1,0)>-2247.89(4,0) Total cholesterol2327.25(6,0)>2321.15(7,0) Non-HDL2366.63(3,0)>2364.71(4,0) HDL-1153.88(6,2)>-1187.08(5,0) Total cholesterol2467.99(1,0)>2464.15(1,0) Non-HDL2462.30(1,0)<2462.92(1,0) HDL1974.43(4,0)>1963.65(5,0) Non-HDL-1024.05(6,3)>-1062.04(2,0) TG1465.47(4,1)>1440.55(1,0) % fat1017.68(5,1)>997.37(3,0) BMI-1714.00(3,0)>-1717.80(2,0) HDL03235.33(11,2)>3192.85(6,0) HDL63567.59(9,1)>3550.43(6,0) Cecum total score652.52(3,1)>634.75(3,0) Percentage of IgM+ B cells1645.30(3,1)>1620.30(2,0)

5. Ping Wang, Mar-02-09 5 QTL Archive Studies (25 traits in 12 studies) TraitsBIC 1 (# main effects,interactions)BIC 2 (# main effects, # interactions) Blood pressure972.65(3,0)>964.16(5,2) Total cholesterol2557.27(4,0)>2554.01(3,0) Non-HDL2267.43(1,0)>2263.60(2,0) B.CecumPC199.20(1,0)>87.49(6,2) B.MidPC1186.17(1,0)>184.76(2,0) B.DistPC1101.29(1,0)>94.76(6,2) C.CecumPC1208.08(2,0)>203.30(3,0) C.DistPC1177.17(2,1)>173.82(5,3) BMD-4711.53(4,0)>-4793.13(7,4) 1: published method; 2: our method.

6. Ping Wang, Mar-02-09 6 QTL Archive Studies GBV Published ResultOur Result ModelD5Mit255 D2Mit151(1.8), D3Mit167(2.5), D5Mit183(3.67), D7Mit246(2.24) BIC-2242.01-2247.89 Malcolm A. Lyons et al. (2003) New quantitative trait loci that contribute to cholesterol gallstone formation detected in an intercross of CAST/Ei and 129S1/SvImJ inbred mice. Physiological Genomics. 14: 225-239.

7. Ping Wang, Mar-02-09 7 QTL Archive Studies

8. Ping Wang, Mar-02-09 8 QTL Archive Studies HDL Published ResultOur Result Model D1Mit159, D1Mit406, D8Mit248, D9Mit129, D12Mit172, D2Mit285, D1Mit159:D1Mit406, D1Mit406:D2Mit285 D1Mit406(9.29), D6Mit86(1.61), D6Mit15(2.68), D9Mit129(2.74), D12Mit172(5.24) BIC-1153.88-1187.08 Naoki Ishimori et al. (2004) Quantitative Trait Loci Analysis for Plasma HDL-Cholesterol Concentrations and Atherosclerosis Susceptibility Between Inbred Mouse Strains C57BL/6J and 129S1/SvImJ. Arterioscler. Thromb. Vasc. Biol. 24: 161-166.

9. Ping Wang, Mar-02-09 9 QTL Archive Studies Hdlq14: D1Mit159 Hdlq15: D1Mit406 Hdlq19: D2Mit285

10. Ping Wang, Mar-02-09 10 QTL Archive Studies HDL: Published ResultOur Result Model D2Mit94, D4Mit110, D6Mit36, D6Mit14 Lineage, D2Mit94(5.97), D4Mit110(6.26), D6Mit14(4.03), D14Mit98(1.33) BIC1974.431963.65 Malcolm A. Lyons et al. (2003) Quantitative trait loci that determine lipoprotein cholesterol levels in DBA/2J and CAST/Ei inbred mice. Journal of Lipid Research. 44: 953-967.

11. Ping Wang, Mar-02-09 11 QTL Archive Studies

12. Ping Wang, Mar-02-09 12 Insulin’s Weighted Model 1984 transcripts’ weighted models overlap with insulin’s weighted model

13. Ping Wang, Mar-02-09 13 Insulin’s Model Plots

14. Ping Wang, Mar-02-09 14 Weighted Model The rest of the vector are 0. Weighted model vector:

15. Ping Wang, Mar-02-09 15 Adjacency Measurement Similarity between weighted models Adjacency measurement

16. Ping Wang, Mar-02-09 16 TOM Distance Topological Overlap Matrix (TOM): defined as reflects the similarity with respect to relationships to all other nodes considered. When defined previously are used here, the relationship refers to co-regulation and co-expression. TOM distance can be used as dissimilarity measurement in clustering.

17. Ping Wang, Mar-02-09 17 1984 transcripts ordered by their adjacency with insulin decreasingly from top.

18. Ping Wang, Mar-02-09 18 500 transcripts ordered by their adjacency with insulin decreasingly from top.

19. Ping Wang, Mar-02-09 19 1984 transcripts clustered using 1-adjacency as distance

20. Ping Wang, Mar-02-09 20 Cluster Identification Using TOM Distance

21. Ping Wang, Mar-02-09 21 1984 transcripts clustered using TOM distance

22. Ping Wang, Mar-02-09 22 Enrichment Test Enrichment test for 1984 transcripts Polyunsaturated fatty acid biosynthesis Glutamate metabolism Regulation of autophagy Butanoate metabolism Methane metabolism Bile acid biosynthesis Fatty acid metabolism (p-value<0.05) Enrichment test for modules e.g., transcripts in yellow module are enriched for Phosphatidylinositol signaling system Long-term depression N-Glycan biosynthesis Gap junction Inositol phosphate metabolism (p-value<0.01)

23. Ping Wang, Mar-02-09 23 Application Paper

24. Ping Wang, Mar-02-09 24 Paper 2: Result Adipose

25. Ping Wang, Mar-02-09 25 Paper 2: Result

26. Ping Wang, Mar-02-09 26 Paper 2: Result

27. Ping Wang, Mar-02-09 27 Insulin is red module

28. Ping Wang, Mar-02-09 28 Paper 2: Result Enrichment tests on transcripts mapping to hot regions. –http://attie.wisc.edu/lab/tools/multiqtl_enrich.phphttp://attie.wisc.edu/lab/tools/multiqtl_enrich.php Enrichment tests on unique transcripts in each module. –Red module are enriched for Phosphatidylinositol signaling system Inositol phosphate metabolism Long-term depression N-Glycan biosynthesis (p-value<0.01) Enrichment tests on transcripts in a specific tissue in each module.