Complex trait analysis, develop-ment, and genomics

1. Complex trait analysis, develop-ment, and genomics The Complex Trait Consortium and the Collaborative Cross Rob Williams, Gary Churchill, and members of the Complex Trait Consortium

2. Elias Zerhouni: The NIH Roadmap. Science 302:63 (2003) Material included in handouts and on the CDalso see www.complextrait.org “Solving the puzzle of complex diseases, from obesity to cancer, will require aholistic understanding of the interplay between factors such as genetics, diet, infectious agents, environment, behavior, and social structures.”

3. What is the CTC A group of ~150 mouse geneticists most of whom have interests in pervasive diseases and differences in disease susceptibility. General Aim: Improve resources for complex trait analysis using mice. Main catalysts and models ENU mutagenesis programs Sequencing and SNP consortia • Catalyze genotyping of strains • Simulation studies of crosses • Planning a collaborative cross • Improved use of resources

4. Established Nov 2001, Edinburgh (n = 20) 1st CTC Conference, May 2002, Memphis (n = 80; hosted by R Williams) CTC Collaborative Cross design workshop, Aug 2002, JHU (K Broman and R Reeves, host) CTC Satellite meeting at IMGC Nov 2003 (n = 40) 2nd CTC Conference, July 2003, Oxford (n = 80; hosted by R Mott and J Flint) CTC strain selection workshop, Sept 2003 (M Daly, host) 3rd CTC Conference, July 2004, TJL The short chronology of the CTC

5. Lusis et al. 2002: Genetic Basis of Common Human Disease Are mouse models appropriate? Yes and No. “If you want to understand where the war on cancer has gone wrong, the mouse is a pretty good place to start.” –Clifton Leaf Fortune, March 2004

6. Mixing mousegenomes (reluctantly) Current practice: Keep it simple: high power with low n

7. Genetic dissection Vp = Vg + Ve Vp = Vg + Ve + 2(Cov GE) + GXE + Vtech Aim 1: Convert genetic variation into a small set of responsible gene loci called QTLs. Aim 2: Develop mechanistic insights into virtually any genetically modulated process or disease.

8. Standard recombinant inbred strains (RI) Standard RI strains female male C57BL/6J (B) DBA/2J (D) BXD fully inbred chromosome pair isogenic F1 hetero- geneous F2 20 generations brother-sister matings Recombined chromosomes are needed for mapping BXD RI Strain set Inbred Isogenic siblings + … + BXD80 BXD2 BXD1

9. Proposal for a Collaborative Cross www.complextrait.org

10. Integrative and cumulative analysis/synthesis physiology anatomy pathology development endocrine profile pharmacokinetics immune 1K Reference environment response pathogens Population metabolism epigenetic modifications proteomics Meta- cancer transcriptome susceptibility analysis

11. Design criteria for a Collaborative Cross • Broad utility: a resource that combines diverse haplotypes and that harbors a broad spectrum of alleles • Freedom from genotyping. Lowering the entry barrier into this field • Unrestricted access to strains, tissues, data, and statistical analysis suites (on-line mapping) • Improved power and precision for trait mapping. Epistasis! • Powerful new approaches to analysis of complex systems. Pleiotropy • Analysis of gene-by-environment interactions • A systems biology resource • A new type of complex animal model to study common human diseases

12. A set of 420 RI lines

13. Mapping with sequence data in hand

14. B6 and D2 haplotype contrast map of Chr 1

15. Celera SNP DB

16. Coincidence analysis !

17. Integrative and cumulative analysis/synthesis physiology anatomy pathology development endocrine profile pharmacokinetics immune 1K Reference environment response pathogens Population metabolism epigenetic modifications proteomics Meta- cancer transcriptome susceptibility analysis

18. QTL/QT gene 6 6 24th www.webqtl.org Wilt Chamberlain: 7 feet 1 inch Willie Shoemaker: 4 feet 11 inches 1.44-fold Phenotypes: from highly complex such as body size to highly specific, such as transcript expression difference

19. Grin2b Cis QTL Trans QTL

20. Ret mRNA correlations in a small data set

21. Ret and Sh3d5

22. Ret GO analysis

23. The App neighborhood Handdrawn sketch of the App neighborhood

24. Associational Networks QTL networks add layer of shared causality

25. Integrative and cumulative analysis/synthesis physiology anatomy pathology development endocrine profile pharmacokinetics immune 1K Reference environment response pathogens Population metabolism epigenetic modifications proteomics Meta- cancer transcriptome susceptibility analysis

26. Cost Components: 24–28 M over 7–8 yrs • Per diem for 8,000 to 10,000 cages (~1500 K/year) • Genotyping intermediate generations (~500 K/year) • Prospective tissue harvesting and cryopreservation (~500 K/year) • Molecular phenotyping of select tissue as proof-of-principle (500 K/year) • Bioinformatics, statistical modeling, administration, colony management (~500 K/year) • Cryopreservation of final lines at F25+ (~200 K) • Sequencing of parental strains (unfunded)

27. NIH Portfolio

28. Lu Lu Elissa Chesler David Airey Siming Shou Jing Gu Yanhua Qu Collaborators Ken Manly (UTHSC) David Threadgill (UNC Chapel Hill) Bob Hitzemann (OHSU) Gary Churchill (TJL) Fernando Pardo Manuel de Villena (UNC) Karl Broman (JHU) Dan Gaile (SUNY Buffalo) Kent Hunter (NCI) Jay Snoddy (ORNL) Jim Cheverud (Wash U) Tim Wiltshire (GNF) Supported by: NIAAA-INIA Program, NIMH, NIDA, and the National Science Foundation (P20-MH 62009), NEI, a Human Brain Project and the William and Dorothy Dunavant Endowment.