The LXS RI strains were derived from the ILS and ISS inbred strains. They have been genotyped using 13,377 SNPs, and some microsatellite markers [108]. 2,659 informative SNPs and microsatellite markers were used for QTL mapping. The CXB panel consists of 13 RI strains derived from C57BL/ 6By and BALB/cBy inbred strains. A total of 1384 informative markers were used for QTL mapping. The B66C3H/HeJ F2 intercrosses have been genotyped using 13,377 SNPs and microsatellite markers, and 8,311 informative markers were used for QTL mapping. Animals and Tissue Acquisition Majority of the BXD and LXS tissues (cerebellum, eye, forebrain, hippocampus, kidney, liver, and striatum for the HQF Illumina dataset) were dissected at the University of Tennessee Health Science Center (UTHSC). Mice were housed at the UTHSC in pathogen-free colonies, at an average of three mice per cage. All animal procedures were approved by the Animal Care and Use Committee. Mice were killed by cervical dislocation, and tissues were rapidly dissected and placed in RNAlater (Ambion, www.ambion.com) and kept overnight at 4u C, and subsequently stored at 280 degree C. Tissue were then processed at UTHSC or shipped to other locations for processing. RNA Isolation and Sample Preparation For the tissues that were processed at UTHSC (all BXD and LXS CNS tissues except HBP Affymetrix striatum), RNA was isolated using RNA STAT-60 (Tel-Test Inc., www.tel-test.com) as per manufacturer’s instructions. Samples were then purified using standard sodium acetate methods prior to microarray hybridiza- tion. The eye samples required additional purification steps to remove eye pigment; this was done using the RNeasy MinElute Cleanup Kit (Qiagen, www.qiagen.com). RNA purity and concentration was evaluated with a spectrophotometer using 260/280 nm absorbance ratio, and RNA quality was checked using Agilent Bioanalyzer 2100 prior to hybridization. Array hybridizations were then done according to standard protocols. Microarray Probe Set Annotation We have re-annotated a majority of Affymetrix probe sets to ensure more accurate description of probe targets. Each probe set represents a concatenations of eleven 25-mer probes, and these have been aligned to the NCBI built 36 version of the mouse genome (mm8 in UCSC Genome Browser) by BLAT analysis. We have also re-annotated the Illumina probes and incorporated these annotations into GeneNetwork. Each probe in the Illumina Mouse–6 and Mouse–6.1 arrays is 50 nucleotides in length, and these have been aligned to NCBI built 36. QTL Mapping We used the strain average expression signal detected by a probe or probe set. QTL mapping was done for all transcripts using QTL Reaper [47]. The mapping algorithm combines simple regression mapping, linear interpolation, and standard Haley- Knott interval mapping [109]. QTL Reaper performs up to a million permutations of an expression trait to calculate the genome-wide empirical p-value and the LOD score associated with a marker. We selected only those transcripts that have highest LOD scores, i.e., genome-wide adjusted best p-values, on markers located on Chr 1 from 172 to 178 Mb. This selected transcripts that are primarily modulated by Qrr1 but excluded transcripts that have QTLs in Qrr1 but have higher LOD scores on markers located on other chromosomal regions. Cis- and trans-QTLs were QTL Hotspot on Mouse Distal Chromosome 1 distinguished based on criteria described by Peirce et al. [47]. To identify trans-QTLs common to multiple datasets, we selected probes/probe sets that target the same genes and have peak LOD scores within 10 Mb in the different datasets. Screening Local QTLs We screened all Affymetrix probe sets with cis-QTLs in Qrr1 for SNPs in target sequences. This step was taken to identity false cis- QTLs caused by differences in hybridization. As probe design is based on the B6 sequence, such spurious cis-QTLs show high expression for the B allele, and low expression for the D allele. Our screening identified only two probe sets in which SNPs result in spurious local QTLs—1429382_at (Tomm40l), and 1452308_a_at (Atp1a2). The majority of cis-QTLs in Qrr1 are likely to be due to actual differences in mRNA abundance. We did not detect a bias in favor of the B allele on cis-regulated expression and the ratio of transcripts with B- and D- positive additive effects is close to 1:1. Analysis of Allele-Specific Expression Difference To measure expression difference between the B and D alleles, we exploited transcribed SNPs to capture allelic expression difference in F1 hybrids [56] using a combination of RT-PCR and a single base extension technology (SNaPshot, Applied Biosystems, www. appliedbiosystems.com). For each transcript we analyzed, Primer 3 [110] was used to design a pair of PCR primers that target sequences on the same exon and flanking an informative SNP. We prepared four pools of RNA from the hippocampus, and four pools of genomic DNA from the spleen of F1 hybrids (male and female B66D2 and D26B6 F1 hybrids). To avoid contamination by genomic DNA, the four RNA pools were treated with Turbo DNase (Ambion, www.ambion.com), and then first strand cDNA was synthesized (GE Healthcare, www. gehealthcare.com). The genomic DNA samples were used as controls, and both cDNA and genomic DNA samples were tested concurrently using the same assay to compare expression levels of B and D transcripts. We amplified the cDNA and genomic DNA samples using GoTaq Flexi DNA polymerase (Promega Corporation, www. promega.com). PCR products were purified using ExoSap-IT (USB Corporation, www.usbweb.com) followed by SNaPshot to extend primer by a single fluorescently labeled ddNTPs. Fluorescently labeled products were purified using calf intestinal phosphatase (CIP, New England BioLabs, www.neb.com) and separated by capillary electrophoresis on ABI3130 (Applied Biosystems). Quantification was done using GeneMapper v4.0 software (Applied Biosystems), and transcript abundance was measured by peak intensities associated with each allele. Ratio of B and D allele in both cDNA and gDNA pools was computed, and t- test (one tail, unequal variance) was done to validate expression difference and polarity of parental alleles. SNP Analysis in Multiple Crosses GeneNetwork has compiled SNP data from different sources— Celera (http://www.celera.com), Perlegen/NIEHS (http:// mouse.perlegen.com/mouse/download.html), BROAD institute (http://www.broad.mit.edu/snp/mouse), Wellcome–CTC [107], dbSNP, and Mouse Phenome Database (http://www.jax.org/ phenome/SNP). SNP counts were done on the GeneNetwork SNP browser. Partial Correlation Analysis A partial correlation is the correlation between X and Y conditioned on one or more control variables. In this study, first PLoS Genetics | www.plosgenetics.org 14 November 2008 | Volume 4 | Issue 11 | e1000260