Presentation is loading. Please wait.

Presentation is loading. Please wait.

Joint analysis of three seemingly independent microarray experiments via multivariate mixed-model equations with null residual covariance structure Antonio.

Similar presentations


Presentation on theme: "Joint analysis of three seemingly independent microarray experiments via multivariate mixed-model equations with null residual covariance structure Antonio."— Presentation transcript:

1 Joint analysis of three seemingly independent microarray experiments via multivariate mixed-model equations with null residual covariance structure Antonio Reverter 1, Yong-Hong Wang 1, Keren A Byrne, Siok Hwee Tan 1, Gregory S Harper 1, Heather L. Bruce 2, and Sigrid A Lehnert 1 The Cooperative Research Centre for Cattle and Beef Quality 1 CSIRO Livestock Industries, Queensland Bioscience Precinct 306 Carmody Rd, St Lucia, QLD 4067, Australia 2 Food Science Australia, Tingalpa DC, QLD 4173, Australia ABSTRACT : A bovine microarray of muscle and fat cDNAs was used in three gene expression experiments (EXP1, EXP2, and EXP3). EXP1 (14 slides) contrasts the gene expression profiles of muscle in Brahman steers fed varying quality diets. EXP2 (12 slides) compares the expression profile in muscle tissue between two breeds. EXP3 (22 slides) studies the mechanisms underlying adipogenesis in vitro. This study undertook to jointly analyse these three experiments using multivariate mixed-models with the relaxed assumption of a non-zero correlation amongst gene expressions across experiments while imposing a null residual covariance structure. Equivalent editing criteria were applied across experiments yielding 1,424,322 intensity records analysed by fitting a tetra-variate model with 263,938 equations and 18 (co)variance components. The latter were estimated by restricted maximum likelihood. Correlation estimates for gene expressions ranged from 0.477  0.004 (for EXP1 and EXP3) to 0.896  0.002 (for EXP1 and EXP2). These moderate to strong estimates indicate the power to be gained with the joint analysis. The expected percentage of differentially expressed genes, as measured from the gene by treatment interaction, was 1.2% for diet in EXP1, 1.3% for breed in EXP2, and 17.1% and 5.1% for age effect and adipogenic treatment, respectively in EXP3. MEDIUM (4  Animals) LOW (3  Anim, 1 Rep) (pooled 3 Anim) HIGH (pooled 2 Anim) MEDIUM (Pool & Ampl) LOW (Pool & Ampl) EXP1: Rockhampton Diets (LD Muscle) TIME 1TIME 2TIME 3 BREED 2 BREED 1 EXP2: Marbling Breeds (LD Muscle) T 1 T 2 T 3 T 4 T 5 T 6 TREAT 1TREAT 2 EXP3: Adipogenesis (in vitro) EXP1EXP2 EXP3 Tot+AmpRNA AmpRNATotRNA AmpRNA Log(Intensity) =Systematic+1,3441,152 6721,440 Gene+9,2459,2459,2459,245 Gene*Trt+ 27,678 45,096 45,474 104,102 Error 405,820 329,247 219,956 469,299 CORRELATION:EXP1 & EXP2 = 0.84 (7,515) EXP1 & EXP3 = 0.56 (8,717) EXP2 & EXP3 = 0.51 (7,316) There is gain to be made from a joint analysis Same Microarray Slide Across the 3 Experiments (48 slides) 4 Variables 1,424,322 Records 263,938 Equations 18 (co)variances REML V(G)9.3 9.7 3.8 8.8 V(G*T) 0.10.11.50.6 V(E)1.41.53.32.0 Differentially Expressed % Total Variation1.2 1.3 17.1 5.1 Actual N (  95% CI) 403 354 n/a 546 RESULTS:Jointly Differentially Expressed UpDownBreed 1 Breed 2Treat 1 Treat 2 Diet Restriction Up 84 02 1 2 1 Down 319 20 5 9 12 Breed 1 121 0 2 2 Breed 2 23315 2 Treat 1 403 0 Treat 2 143 IMPLICATIONS Go beyond standard applications: Pleiotropic Patterns of Co-Regulation Evolution Plasticity MODEL:


Download ppt "Joint analysis of three seemingly independent microarray experiments via multivariate mixed-model equations with null residual covariance structure Antonio."

Similar presentations


Ads by Google