Global Mouse mRNA and Protein Levels Comparison Figure 1. A schematic representation of the experimental design. 97 inbred and recombinant inbred strains in the HMDP panel were utilized to study the relationships between transcripts, proteins, and clinical traits. The relationships between proteins and transcripts were assessed at the biological level by the overall correlation across datasets, and at the genetic level by comparing the genome-wide association profiles of the two datasets. The biological relationship between the transcripts and proteins was also assessed in the context of the physiological phenotypes by relating these two datasets to the 42 clinical traits measured in the HMDP panel. doi:10.1371/journal.pgen.1001393.g001 genetic variation in the peptide levels as well as the degree of nongenetic/technical variations in peptide quantification. Thus, we defined a ‘‘signal to noise’’ measure for each peptide as the ratio of the total variance in the HMDP over the variance in the ten replicates. The variance in the ten replicates would be due to nongenetic biologic variance as well as technical variance (herein termed ‘‘noise’’) while the total HMDP variance would include genetic variance, nongenetic biologic variance, and technical variance. Accordingly, a large value of signal to noise could either mean large genetic variation, small nongenetic variation, or both. Conversely, a smaller value for signal to noise would either mean small genetic variation, large nongenetic variation, or both. As can be seen in Figure 2B, signal to noise ratios varied significantly across different peptides. We complemented the LC/MS studies for a small set of proteins (11) by performing immunoblot quantitation in 9 of the HMDP strains. Over half of the peptides exhibited significant discrepancies in relative levels using the two methods and those with small ‘‘signal to noise’’ ratios (small genetic variation and/or large noise component) exhibited reduced correlations with the immunoblotting results (p-value = 3.361025). Although immuno- blotting is semi-quantitative, these results suggest that peptides with a large signal to noise ratio will provide the best estimates of the true relationship between RNA levels and protein levels. (Immunoblot results are presented in Table S1, Table S2, and Figure S1). Transcript levels in inbred stains were measured by profiling three mice for each strain, using Affymetrix MOE430A platform, and taking the average of expression over the three biological replicates. This design provided us with an opportunity to a) better estimate the ‘‘true’’ values for the mRNA levels in each strain and b) estimate the heritability of each probeset across the HMDP population. The distribution of heritability estimates is shown in Figure 2C. Consistent with previous reports [16], we detected a broad spectrum of heritability estimates for the transcript levels ranging from 0.07 to 0.95. Using ANOVA, we assigned significance to the heritability values obtained for each probeset and found that for as many as 50% of the probesets (11248 probesets), there was a significant (p-value,0.05 for strain term) genetic component affecting the transcript levels. Previous reports have documented conflicting results about the reproducibility measurements generated by microarray platforms [17–21]. To investigate this in our dataset, we compared the expression levels measured by the Affymetrix microarray to the expression levels measured by next generation sequencing (NGS) in small subset of inbred strains. Using Illumina’s Genome Analyzer we profiled the liver transcriptome of one C57BL/6J and one DBA/2J mouse and generated ,17,000,000 sequences for the fragmented mRNAs for each strain. Using Tophat [22] and Cufflink [23] algorithms, we were able to uniquely align and count 4,800,000 and 7,000,000 sequences for C57BL/6J and DBA/2J respectively (See Materials and Methods). After sequence align- ment and quantification of the read counts, we compared the transcriptome of the each strain against the microarray data generated by the Affymetrix MOE430a platform (Figure 2D). This comparison revealed a high concordance between the data obtained from two technologies (Spearman correlation coefficient of 0.69 for both C57BL/6J and DBA/2 samples). These results were similar to a previous cross-platform comparative study [24] and indicated that, for most transcripts, microarray data produce a highly reliable estimate of transcript levels. Based on the results reported above, in order to enrich for high quality data and provide a better estimate of true relationships between transcript and protein data, we focused on transcript and peptide data with significant genetic and biological variation. For peptide data, we used the signal to noise ratio parameter to further filter the noisy peptides from our dataset. The cutoff we chose for filtering peptides was a signal to noise ratio of 2. After removing PLoS Genetics | www.plosgenetics.org 3 June 2011 | Volume 7 | Issue 6 | e1001393