Multiple Traits & Microarrays

Transcription

1 Multiple Traits & Micrarrays 1. why study multiple traits tgether? 2-13 diabetes case study central dgma via micrarrays 2. design issues fr expensive phentypes selective phentyping 3. why are traits crrelated? clse linkage r pleitrpy? 4. hw t handle high thrughput? dimensin reductin: multivariate stats principal cmpnents n phentypes Traits NCSU QTL II: Yandell

2 1. why study multiple traits tgether? avid reductinist apprach t bilgy address physilgical/bichemical mechanisms Schmalhausen (1942); Falcner (1952) separate clse linkage frm pleitrpy 1 lcus r 2 linked lci? identify epistatic interactin r canalizatin influence f genetic backgrund establish QTL x envirnment interactins decmpse genetic crrelatin amng traits increase pwer t detect QTL Traits NCSU QTL II: Yandell

3 Type 2 Diabetes Mellitus Traits NCSU QTL II: Yandell

4 Insulin Requirement decmpensatin frm Traits Unger & Orci FASEB J. (2001) 15,312 NCSU QTL II: Yandell

5 glucse insulin (curtesy AD Attie) Traits NCSU QTL II: Yandell

6 studying diabetes in an F2 segregating crss f inbred lines B6.b x BTBR.b F1 F2 selected mice with b/b alleles at leptin gene (chr 6) measured and mapped bdy weight, insulin, glucse at varius ages (Stehr et al Diabetes) sacrificed at 14 weeks, tissues preserved gene expressin data Affymetrix micrarrays n parental strains, F1 (Nadler et al PNAS; Ntambi et al PNAS) RT-PCR fr a few mrna n 108 F2 mice liver tissues (Lan et al Diabetes; Lan et al Genetics) Affymetrix micrarrays n 60 F2 mice liver tissues design (Jin et al Genetics tent. accept) analysis (wrk in prep.) Traits NCSU QTL II: Yandell

7 why map gene expressin as a quantitative trait? cis-r trans-actin? des gene cntrl its wn expressin? r is it influenced by ne r mre ther genmic regins? evidence fr bth mdes (Brem et al Science) simultaneusly measure all mrna in a tissue ~5,000 mrna active per cell n average ~30,000 genes in genme use genetic recmbinatin as natural experiment mechanics f gene expressin mapping measure gene expressin in intercrss (F2) ppulatin map expressin as quantitative trait (QTL) adjust fr multiple testing Traits NCSU QTL II: Yandell

8 LOD map fr PDI: cis-regulatin (Lan et al. 2003) Traits NCSU QTL II: Yandell

9 mapping micrarray data single gene expressin as trait (single QTL) Dumas et al. (2000 J Hypertens) verview, wish lists Jansen, Nap (2001 Trends Gen); Cheung, Spielman (2002); Derge (2002 Nat Rev Gen); Bchner (2003 Nat Rev Gen) micrarray scan via 1 QTL interval mapping Brem et al. (2002 Science); Schadt et al. (2003 Nature); Yvert et al. (2003 Nat Gen) fund putative cis- and trans- acting genes multivariate and multiple QTL apprach Lan et al. (2003 Genetics) Traits NCSU QTL II: Yandell

10 central dgma via micrarrays (Bchner 2003) Traits NCSU QTL II: Yandell

11 idea f mapping micrarrays (Jansen Nap 2001) Traits NCSU QTL II: Yandell

12 gal: unravel bichemical pathways (Jansen Nap 2001) Traits NCSU QTL II: Yandell

13 Traits NCSU QTL II: Yandell

14 2. design issues fr expensive phentypes (thanks t CF Amy Jin) micrarray analysis ~ $1000 per muse can nly affrd t assay 60 f 108 in panel wish t nt lse much pwer t detect QTL selective phentyping gentype all individuals in panel select subset fr phentyping previus studies can prvide guide Traits NCSU QTL II: Yandell

15 simulated LOD prfiles with 3 QTL Traits NCSU QTL II: Yandell Map psitin

16 selective phentyping gentype all individuals in panel whle genme r selected genmic regins? maintain high pwer in selected regins sensitivity similar t randm sample in ther regins select subset fr phentyping select individuals with large genetic distance use experimental design cncepts (Jin et al. 2004) previus studies: key regins f chr 2,4,5,9,16,19 QTL fr imprtant physilgical traits Traits NCSU QTL II: Yandell

17 cmparisn f different selectin methds sensitivity = pr( detect QTL QTL is real ) sensitivity f f mc m g r gc r f m c g r f m c g r f m c g full data marker-based chr-based genme-based randm r f m c g r Number f chrmsmes examined Traits NCSU QTL II: Yandell

18 LOD prfile f SCD trait 5 4 full data marker-based randm ld Traits NCSU QTL II: Yandell Map psitin

19 multidimensinal scaling f mice selectin (clse pints have similar gentypes) Traits NCSU QTL II: Yandell Pi i l t1(23%)

20 is this relevant t large QTL studies? why nt phentype entire mapping panel? selectively phentype subset f 50-67% may capture mst effects with little lss f pwer tw-stage selective phentyping? gentype & phentype subset f culd selectively phentype using whle genme QTL map t identify key genmic regins selectively phentype subset using key regins Traits NCSU QTL II: Yandell

21 sensitivity = pr( detect QTL QTL is real ) depends n heritability and prprtin sampled (f N=100) sensitivity H=0.245 H=0.50 H= sample size n Traits NCSU QTL II: Yandell

22 3. why are traits crrelated? envirnmental crrelatin nn-genetic, cntrllable by design histrical crrelatin (learned behavir) physilgical crrelatin (same bdy) genetic crrelatin pleitrpy ne gene, many functins cmmn bichemical pathway, splicing variants clse linkage tw tightly linked genes gentypes Q are cllinear Traits NCSU QTL II: Yandell

23 interplay f pleitrpy & crrelatin pleitrpy nly crrelatin nly Krl et al. (2001) bth Traits NCSU QTL II: Yandell

24 3 crrelated traits (Jiang Zeng 1995) ellipses centered n gentypic value width fr nminal frequency main axis angle envirnmental crrelatin 3 QTL, F2 ρ P = 0.3, ρ G = 0.54, ρ E = gentypes nte signs f genetic and envirnmental crrelatin jiang jiang jiang ρ P = 0.06, ρ G = 0.68, ρ E = jiang3 ρ P = -0.07, ρ G = -0.22, ρ E = jiang2 jiang3 Traits NCSU QTL II: Yandell

25 pleitrpy r clse linkage? 2 traits, 2 qtl/trait 54cM 114,128cM Jiang Zeng (1995) Traits NCSU QTL II: Yandell

26 QTL x sex interactin (Vieira et al. 2000) Traits NCSU QTL II: Yandell

27 4. high thrughput dilemma want t fcus n gene expressin netwrk ideally capture pathway in a few dimensins allw fr cmplicated genetic architecture may have multiple cntrlling lci culd affect many genes in crdinated fashin culd shw evidence f epistasis quick assessment via interval mapping may be misleading try mapping principle cmpnents as super-traits capture key multivariate features f multiple traits elicit bichemical pathways (Hendersn et al. Heschele 2001; Ong Page 2002) Traits NCSU QTL II: Yandell

28 expressin pleitrpy in yeast genme (Brem et al. 2002) crdinated expressin in muse genme (Schadt et al. 2003) Traits NCSU QTL II: Yandell

29 high thrughput: which genes are the key players? clustering f expressin seed by insulin, glucse advantage: subset relevant t trait disadvantage: still many genes t study Traits NCSU QTL II: Yandell

30 SCD1, FAS,GPAT, PEPCK: trans-regulatin by multiple QTL? 4 3 ld LOD ch2 ch5 ch9 Traits NCSU QTL II: Yandell

31 frm gene expressin t super-genes PC r SVD decmpsitin f multiple traits Y = t traits n individuals decmpse as Y = UDW T U,W = rth-nrmal transfrms (eigen-vectrs) D = diagnal matrix with singular values transfrm prblem t principal cmpnents W 1 and W 2 uncrrelated "super-traits" interval map each PC separately W 1 = µ * 1 G * 1Q e * 1 may nly need t map a few PCs Traits NCSU QTL II: Yandell

32 PC simply rtates & rescales t find majr axes f variatin mrna V mrna V1 Traits NCSU QTL II: Yandell

33 QTL via Principal Cmpnents Drsphila gnad shape Liu et al. (1996); Zeng et al. (2000) ther refs f interest Weller et al. (1996); Mangin et al. (1998); Olsn et al. (1999); Mahler et al. (2002) prblems PC may have n relatin t genetics! residuals frm QTL crrelated acrss PCs PC is descriptive summary, nt interpretive Traits NCSU QTL II: Yandell

34 multivariate screen fr gene expressing mapping principal cmpnents PC1(red) and SCD(black) PC2 (22%) PC1 (42%) Traits NCSU QTL II: Yandell

35 mapping first diabetes PC as a trait lci histgram hng7pc.bim summaries with pattern ch2,ch5,ch9 ch2 ch5 ch additive ch2 ch5 ch dminance ch2 ch5 ch Traits NCSU QTL II: Yandell

36 pfdr fr PC1 analysis relative size f HPD regin pr( lcus in HPD m>0 ) Traits NCSU QTL II: Yandell pr( H=0 p>size ) BH pfdr(-) and size(.) Strey pfdr(-) prir prbability fractin f psterir fund in tails

37 PC acrss micrarray functinal grups 1500 mrna f 30, functinal grups 60 mice 2-35 mrna / grup which are interesting? examine PC1, PC2 size = # unique mrna Traits NCSU QTL II: Yandell

38 PC-guided search f mrna (red lines at main QTL fr PC1) 2-marker gentype scantw phentype Traits NCSU QTL II: Yandell

39 Traits NCSU QTL II: Yandell imprvements n PC? what is ur gal? reduce dimensinality fcus n QTL PC reduces dimensinality but may nt relate t genetics cannical discriminant analysis rtate t imprve discriminatin red at each putative QTL Gilbert and le Ry (2003,2004)

40 hw t map multiple traits? WinQTL/QTL Cartgrapher: IM & CIM Jiang Zeng (1995); statgen.ncsu.edu/qtlcart MultiQTL: 1-2 QTL with PC n residuals Krl et al. (2001); QTL with DA acrss traits Gilbert and le Ry (2003, 2004) QTL Express: Haley-Kntt regressin Kntt Haley (2000); qtl.cap.ed.ac.uk SOLAR: utbred pedigrees Almasy Blanger (1997); Williams et al. (1999) Traits NCSU QTL II: Yandell