Artificial Degradation of Reference RNA
Ambion® human reference brain RNA and Stratagene® reference pooled RNA samples were heated at 95°C for 0, 10, 30, and 60 minutes to artificially degrade them. Samples were analyzed using BioAnalyzer® (Agilent Technologies) to visualize levels of degradation (Additional File 1). Combinations of 75% brain reference RNA and 25% pooled reference RNA, and 75% pooled reference RNA and 25% brain reference RNA were also mixed for comparison with pure samples. Samples were then prepared for profiling on microarray platforms as described below.
Frozen and formalin-fixed postmortem human brain samples for gene expression profiling
57 frozen blocks of fresh frozen brain tissue and 4 blocks of formalin-fixed brain tissue from the prefrontal cortex of controls and autistic, male and female cases were obtained from the Harvard Brain and Tissue Resource Center (United States Public Health Service) and from the University of Miami/University of Maryland Brain and Tissue Bank (National Institute of Child Health and Human Development; Table 1).
Diagnostic criteria of Autistic Disorder was verified for all autistic cases by review of psychological and medical records, including the Autism Diagnostic Interview-Revised (; ADI-R), and the Autism Diagnostic Observation Schedule (; ADOS) by a psychologist with extensive diagnostic experience with autism (CCB; Table 1). Seizure incidence of autistic cases was also assessed through case records.
All cases were deceased, and were deidentified by the brain banks where tissue was obtained. However, the same human protections procedures were employed as for live subjects. Research procedures employed in this study were approved by the institutional review board of the University of California, San Diego (protocol number 091205).
Brain sample collection
Due to documented variability of gene expression in neighboring brain areas [19, 20], it is of extreme importance that the blocks of tissue chosen for gene expression profiling are from comparable regions between cases. Anatomical landmarks were identified as consistently as possible for dissection across cases with the goal of obtaining a set of highly controlled, comparable tissue for brain gene expression profiling. When available, tissue from the superior frontal gyrus of the dorsal lateral prefrontal cortex (DLPFC) was dissected in each case. When this area was not available, we sampled from the middle frontal gyrus. The formalin-fixed samples were obtained from larger areas of frontal cortex. Cytoarchitecture and anatomical landmarks were also used to determine the area of DLPFC similar to that of the frozen tissue for dissection.
RNA Extraction from Tissues
Extraction of total RNA from 5-10 mg of frozen tissue from both grey and white matter, with as many layers of cortex as possible, was performed using MELT® kit from Ambion according to manufacturer's instructions (http://www.ambion.com). Extraction of total RNA from 5-10 mg of formalin-fixed tissue sections was performed using the Roche® High Pure FFPE RNA Micro Kit. Select RNA samples were analyzed with BioAnalyzer® (Agilent) according to the manufacturer's protocol for quality control and quantification, and available RNA Integrity Numbers (RIN) are reported in Table 1. Whole RNA from remaining samples was quantified using a NanoDrop® spectrophotometer.
DASL Labeling, Hybridization, and Scanning
Total RNA from reference samples, frozen, and formalin-fixed cases underwent cDNA synthesis, and cDNA-mediated annealing, selection, and ligation (DASL)-based labeling, hybridization to Illumina HumanRef8 v3 and Human 12K microarrays (DASL assay on reference RNA samples only), and scanning on two separate occasions as described previously . Both biological and technical replicates were included for quality control. Using biotinylated random primers and oligo-dT, 200 ng RNA was converted to cDNA. The biotinylated cDNA was then immobilized to a streptavidin-coated solid support, and annealed with a pool of gene-specific oligonucleotides.
Following extension and ligation, the ligated oligonucleotides were PCR amplified with a biotinylated and a fluorophore-labeled universal primer, and captured using streptavidin paramagnetic beads. Finally, the single-stranded PCR products were eluted and hybridized to the BeadChips at 58°C for 16 hours. A BeadArray Reader was used to scan array images and extract fluorescence intensities, and all data were uploaded into BeadStudio software without normalization or background subtraction for quality control and processing. All raw data is available on the NCBI Gene Expression Omnibus under accession number GSE28475 (http://www.ncbi.nlm.nih.gov/geo/).
IVT Labeling, Hybridization, and Scanning
Gene expression profiling was performed on RNA from reference samples, frozen, and fixed cases using the Illumina Human Ref-8 v3 Expression BeadChip platform (Illumina Inc., San Diego, CA, USA) according to manufacturer's protocols. Following RNA extraction, an IVT reaction for biotinylated cRNA was performed overnight (~16 h). 750 ng cRNA were hybridized on the beadchip at 58°C overnight and detected with Cyanine3-streptavidin. Arrays were again scanned with the Illumina BeadArray Reader and read into Illumina GenomeStudio software without normalization or background subtraction.
Microarray data analysis
All data analyzed were raw and unprocessed. Probe detection and signal information was directly output from GenomeStudio. Probe concordance and self-reproducibility were calculated based on technical replicates in each category (frozen tissue-RNA assayed by IVT, frozen tissue-RNA assayed by DASL, fixed tissue-RNA assayed by IVT, fixed tissue-RNA assayed by DASL).
All plots were generated using the R/Bioconductor package Lumi [21–23] and Microsoft Excel. Cluster dendrograms were generated by Lumi using Euclidean distance and average linkage clustering.
Multivariate Distance Matrix Regression
To assess the variance within the dataset attributable to a set of variables before and after manipulating and pre-processing the expression assay results (e.g. batch correction), multivariate distance matrix regression (MDMR; ) with 1000 permutations was applied to the Euclidean distance matrices constructed from the expression values between each sample (http://polymorphism.scripps.edu/~cabney/cgi-bin/mmr.cgi). Variables of interest that were related to the expression profiles reflected in the distance matrices included batch, RNA source (reference RNA, frozen tissue, formalin-fixed tissue), assay type (DASL or IVT), gender, diagnosis, and age of cases from which we sampled. We leveraged both single independent variable and multiple independent MDMR results. Case data analyzed by MDMR as predictors (diagnosis, age, seizures) were compiled by a clinical psychologist (C.C.B).
Independent qPCR Validation of Microarray Results
Genes and Cases
RNA from 1 male autistic and 1 male control case of 31 years was analyzed using SYBR green RT-PCR to validate the intensity values detected by microarray. 19 genes were chosen with a wide range of fold change values (positive and negative), and are listed in Table 2. Using Primer3 software , primers of these genes were designed across splice junctions to avoid artifacts by genomic DNA contamination and to produce amplicons of ~200 bp. RPL13A, B2M and ACTB, three genes highly expressed in the brain at stable levels  were chosen as reference genes for each experiment. Expression values for the remainder of the genes were normalized to these reference gene controls.
cDNA Synthesis and qPCR
One microgram of total RNA was used for cDNA synthesis using random hexamers and AMV reverse transcriptase. An equivalent of 50 ng of RNA was processed by qPCR using Roche's LightCycler rapid thermal cycler system (Roche Diagnostics Ltd, Lewes, UK) according to the manufacturer's instructions, in a 96-well, 10-uL format using standard PCR conditions. 1 μL of cDNA template, 250 nM of forward and reverse primer, and 5 μL of qPCR Master Mix (Roche) were mixed for each reaction.
According to Vandesompele et al.,  we took the geometric mean of all reference genes and the difference between this mean and the average intensity of experimental genes to find the delta Ct for each experimental gene. Subsequently, log2 fold change was assessed using -(T-C) where T = delta Ct of gene of the autistic case, and C = delta Ct of gene of the control case. Spearman's rank correlation was then applied to the results from the qPCR and microarray assays.