quantified by Solexa sequencing from Wang et al [53]. The expression values from the six samples for cerebellum were averaged. Gene expression was measured in ‘number of sequenced reads per kilobase of exon per million mapped reads’ (RPKM) [64]. We considered genes with $0.5 RPKM in a tissue as expressed in that tissue. As tissue-specific genes we defined those with expression above the threshold in one out of ten tissues. We retrieved ubiquitously expressed (housekeeping) human genes from Ramskold et al [65]. mRNA retention in mature sperm The abundance of mRNA in mature sperm from 13 different fertile donors was measured using Affymetrix gene expression microarrays by Platts et al [66]. We downloaded the mRNA detection calls (mRNA present/absent calculated by DChip MBE) for each gene from GEO. Probe to gene mappings were made using Ensembl and probes matching multiple genes were removed. We defined a gene’s mRNA as present in mature sperm if at least one probe matching this gene showed expression present in at least 7 out of 13 sperm donors. Gene function annotations Gene ontology (GO) annotations of genes were obtained from Ensembl. Genes coding for developmental transcription factors were defined as genes annotated with the Biological Process term ‘‘DNA- dependent regulation of cellular transcription’’ (GO:0006355) and also with a term that contains the word ‘‘development.’’ Predicting nucleosome retention across the human genome To test the performance of GC-content as a predictor of nucleosome retention throughout the human genome we used all non-repetitive 150 bp windows of the genome. We further excluded windows that had in total less than 5 sequenced reads from the nucleosome and the genomic control datasets, as low-read count windows were also excluded from the nucleosome retention peak finding algorithm used by Hammoud et al. This analysis was also performed separately for genic and non-genic windows (here 1 kb upstream of each start site was included in the genic portion of the genome). Receiver operating characteristic (ROC) analysis was used to assess how well we can predict the regions of nucleosome retention enrichment in sperm from GC- and CpG-content. ROC analysis was performed in R using the ROCR package [67]. In brief, all 150 bp windows of the genome were ranked according to decreasing GC (or CpG) count. Going down this ranked list, we then counted the number of windows overlapping regions of nucleosome retention as a fraction of all windows with the same or higher GC-content (true positive rate, y-axis) and the number of windows not overlapping regions of nucleosome retention as a fraction of all windows with lower GC-content (false positive rate, x- axis). If there were no correlation between GC-content and nucleosome retention in sperm, we would expect the ROC curve to be a diagonal line across the plot and the resulting area under the curve to be equal to 0.5. For a perfect predictor, the area under the curve would be equal to 1. In Figure 1, for direct comparison, we also plotted the sensitivity and specificity of CpG islands in predicting 150-bp windows that overlap regions of nucleosome retention in sperm. CpG islands as defined by Gardiner-Garden et al [36] were downloaded from the UCSC genome browser database. DNase I hypersensitive sites in human embryonic stem cells We retrieved the locations of DNase I hypersensitive sites for H1 human embryonic stem cells [68] from Ensembl (release 60) Nucleosome Retention in Human Sperm and converted the locations to human genome version hg18 using the UCSC LiftOver tool. All sites within 1 kb from any type of annotated gene in Ensembl were removed. We retained 64,217 noncoding ES DNase I hypersensitive sites. Average signals were calculated for 4 kb centered on the middle positions of these sites. DNA methylation annotation of CpG islands in human embryonic stem cells We used the DNA methylation status annotation of CpG islands reported in Straussman et al [41]. We considered only CpG islands that were consistently annotated as DNA methylated or unmethy- lated in both embryonic stem cell lines (I6 and H13) tested by Straussman et al. Average signals were calculated for 4 kb regions centered at the middle position of the islands. Supporting Information Figure S1 Correlations between GC-content and nucleosome to protamine normalized probe signal intensity ratio. The two plots show the correlation for the data generated by two different experimental methods of identifying nucleosome enriched regions from Arpanahi et al; micrococcal nuclease digestion (MND, A) and salt-extraction followed by restriction digestion (SRD, B). In both cases the probe value corresponds to the ratio of the nucleosome to protamine normalized signal intensity. The GC-content shown corresponds to the window 6147 bp from the microarray probe. (EPS) Figure S2 Nucleosomes are preferentially retained in sperm at transcription start sites. (A) Genome-wide distribution of nucleo- some retention sites. Nucleosome enrichment regions are classified according to whether they are within 50 bp of a transcription start site (TSS, 9,068 regions), or end site (TES, 718 regions), overlapping other parts of a gene (other genic, 7,785) or other parts of the genome (non-genic, 7,549). The coordinates of regions of nucleosome retention defined by sequencing were retrieved from Hammoud et al. (B) The plot shows the percentage of transcription start and end sites that are within 50 bp of a nucleosome retention region. The total number of human (Ensembl) transcripts considered here is 52,312. Error bars indicate 95% confidence intervals. (EPS) Figure S3 Nucleosome retention at transcription start sites correlates with the expression breadth of a gene rather than the expression level in the germline. (A) There is a positive trend in the proportion of genes that have retained nucleosomes at the start site and the expression level of the gene in testes (1,589 genes per bin, x2 -test for trend in proportions = 626.1, p-value,2.2610216). (B) However, there is also a strong positive correlation between expression breadth (the number of different tissues in which a gene is expressed) and nucleosome retention at the start site (x2 -test for trend in proportions = 1,303.7, p-value,2.2610216). The total number of genes (and the number of genes with nucleosomes retained at the start) in each bin are as follows: 0-tissues = 792 (125), 1-tissue = 1472 (313), 2-tissues = 835 (284), 3-tissues = 742 (316), 4-tissues = 653 (264), 5-tissues = 562 (251), 6-tissues = 617 (287), 7-tissues = 657 (324), 8-tissues = 817 (433), 9-tissues = 1248 (711), 10-tissues = 7502 (4555). (C) The correlation between nucleosome retention at the start and expression level is largely explained by expression breadth. Here, we test the correlation between expression level and nucleosome retention at the start of genes, when controlling for expression breadth. In C, each panel corresponds to the genes in each expression breadth shown in PLoS Genetics | www.plosgenetics.org 9 April 2011 | Volume 7 | Issue 4 | e1002036