Fontanesi et al. BMC Genomics 2010, 11:639 http://www.biomedcentral.com/1471-2164/11/639 by both Cy5 and Cy3) was carried out in another array. Hybridization and array scanning were performed by Roche NimbleGen as previously described [39]. Data normalization was conducted using the normalize.qsline method from the Bioconductor package in R [39]. Then data were analysed for each hybridization using normal- ized log2 ratios using the CGHweb server (http://comp- bio.med.harvard.edu/CGHweb/[77]) that includes multiple algorithms. We used the self-self hybridisation and the BTA13 control region to define a suitable threshold to apply to the CGHweb calls in order to minimize false positives. Specifically we retained pre- dicted CNVs if it had at least five consecutives data- points supporting it (considering an average of probe values inside a smoothing window of five), thus limiting the minimum CNV size to about 30 kb, even if this resolution can vary in different regions depending on the relative distance of the probes that can be different from the averaged ~6 kb. Pointwise averaging of all computed profiles and maps of gains/losses for smoothed/segmented obtained from several algorithms (Lowess, Wavelet, Quantreg, ruavg, CBS, CGHseg, BioHMM, cghFLasso, GLAD, and FASeg) and summary data were generated. Pointwise averaging was shown to have good performances in calling alteration of copy number [91] and was chosen to compensate possible signal differences among probes in the cattle-goat het- erologous experiment. Summary data were considered to call gain/loss in a chromosome region and to compile a high confidence set of CNVs. Then CNVs were called considering a conservative approach joining regions of at least 4-5 contiguous probes with CNV signal sepa- rated by up to three probes without CNV signal in the same individual (Additional file 1). This adjustment was applied in order to overcome possible signal losses or hybridisation problems in the cross-species aCGH experiment. CNVRs were reported aggregating overlap- ping or partially overlapping CNVs in different animals as previously reported [28,51] and applying the same criteria for CNVs within individuals (Additional file 2). The false discovery rate (FDR) was estimated based on the observation of 2 false positives in the self-self hybri- disation. A rough estimate of the FDR is the expected number of false positives per array (n. 2) times the num- ber of total arrays divided by the total number of CNVs (n. 161), resulting in an estimated FDR of 11%. This cal- culation should be considered only an approximation because it does not consider the potential for varying false positive rates across arrays. Based on these criteria the averaged log2 ratio threshold to call gains and losses [77] was empirically established at 0.175 considering the results obtained for the ASIP gene region. Four goats out of five with independent validated CNV [22] in this gene reported an averaged log2 ratio > 0.175, therefore Page 10 of 15 this value was used as threshold even if in another goat the averaged log2 ratio for the ASIP region was 0.156. However, even if this latter value did not change the self-self FDR results, we used as threshold the value of 0.175 because the self-self hybridization could not fully reflect the variance of our 9 test experiments and we preferred a low false-positive rate even at the expense of having more false negatives in our dataset. Validation of CNVs Validation of CNVs was performed by semiquantitative fluorescent multiplex PCR (SQF-PCR) as previously reported [22,92] using genomic DNA of the same goats analysed in the aCGH experiment and genomic DNA of additional goats (additional 8 Saanaen, 12 Girgentana, and 14 Murciano-Granadina) extracted as reported above. Briefly, two internal control regions known to have no CNV (DGAT1 and MC1R gene fragments) and CNVRs of interest were co-amplified in multiplex PCR under quantitative PCR conditions (with forward pri- mers labelled in 5’ with 6FAM) and the products were separated by capillary electrophoresis using an ABI3100 Avant sequencer (Applied Biosystems, Foster City, CA, USA) [22]. Peak heights of regions of interest were nor- malized against those of the internal controls. Primer pairs for control gene fragments and analysed CNVRs are reported in Additional file 6. SQF-PCR was per- formed in a total volume of 10 μL using 1-6 pmol of each primer and the conditions reported in Additional file 6. PCR profile was as follows: 5 min at 95°C; 20-22 amplification cycles of 30 sec at 95°C, 30 sec at 59°C, 30 sec at 72°C; 5 min at 72°C. Capillary electrophoresis was performed using 1 μL of reaction product, diluted in 10 μL of Hi-Di formamide (Applied Biosystems), and added with 0.1 μL of Rox labelled DNA ladder (500HD Rox, Applied Biosystems). Peak heights were obtained using GeneScan software v. 3.7 (Applied Biosystems). DNA dosages were calculated by comparing the normalized peak height ratios of goats of interest with the average normalized ratios of the reference Camosciata delle Alpi goat as follows: the peak height of a fragment of interest was divided by the peak height of the internal control; the averaged value obtained from at least two analyses for each sample/target region was divided by the same averaged value obtained for the control goat DNA. We adopted the theoretical values of 1.5, 2.0, 2.5, and so on for a gain of multiple of one, two, three or other copies, respectively, compared to the copy content (unknown) of the reference DNA sample. Similarly, a loss of one set of copies (or one copy in case of a simple duplica- tion) would theoretically result in a value of 0.5. These values should be considered only approximation of the copy number content as the objective was to validate the results obtained with aCGH and not to precisely