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Profiling DNA Methylation Differences Between Inbred Mouse Strains On bioRxiv preprint doi: https://doi.org/10.1101/194464; this version posted September 27, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Profiling DNA Methylation Differences Between Inbred Mouse Strains 2 on the Illumina Human Infinium MethylationEPIC Microarray 3 Short title: Cross-species utility of human DNA methylation microarray 4 Hemant Gujar1, Jane W. Liang1, Nicholas C. Wong2, Khyobeni Mozhui1,3* 5 6 1 Department of Preventive Medicine, University of Tennessee Health Science Center, 7 Memphis, Tennessee 38163, USA 8 2 Monash Bioinformatics Platform, Monash University, Clayton VIC, Australia 9 3 Department of Genetics, Genomics and Informatics, University of Tennessee Health 10 Science Centre, Memphis, Tennessee 38163, USA 11 * Corresponding author 12 Khyobeni Mozhui 13 Department of Preventive Medicine, College of Medicine 14 University of Tennessee Health Science Center 15 66 N. Pauline Street, #631 16 Memphis, TN 38163 17 Phone no. 901-448-7334 18 Email: [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/194464; this version posted September 27, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 19 Abstract 20 The Illumina Infinium MethylationEPIC provides an efficient platform for profiling DNA 21 methylation in humans at over 850,000 CpGs. Model organisms such as mice do not 22 currently benefit from an equivalent array. Here we used this array to measure DNA 23 methylation in mice. We defined probes targeting conserved regions and performed a 24 comparison between the array-based assay and affinity-based DNA sequencing of 25 methyl-CpGs (MBD-seq). Mouse samples consisted of 11 liver DNA from two strains, 26 C57BL/6J (B6) and DBA/2J (D2), that varied widely in age. Linear regression was 27 applied to detect differential methylation. In total, 13,665 probes (1.6% of total probes) 28 aligned to conserved CpGs. Beta-values (β-value) for these probes showed a 29 distribution similar to that in humans. Overall, there was high concordance in 30 methylation signal between the EPIC array and MBD-seq (Pearson correlation r = 0.70, 31 p-value < 0.0001). However, the EPIC probes had higher quantitative sensitivity at 32 CpGs that are hypo- (β-value < 0.3) or hypermethylated (β-value > 0.7). In terms of 33 differential methylation, no EPIC probe detected significant difference between age 34 groups at a Benjamini-Hochberg threshold of 10%, and the MBD-seq performed better 35 at detecting age-dependent change in methylation. However, the top most significant 36 probe for age (cg13269407; uncorrected p-value = 1.8 x 10-5) is part of the clock CpGs 37 used to estimate the human epigenetic age. For strain, 219 Infinium probes detected 38 significant differential methylation (FDR cutoff 10%) with ~80% CpGs associated with 39 higher methylation in D2. This higher methylation profile in D2 compared to B6 was also 40 replicated by the MBD-seq data. To summarize, we found only a small subset of EPIC 41 probes that target conserved sites. However, for this small subset the array provides a 2 bioRxiv preprint doi: https://doi.org/10.1101/194464; this version posted September 27, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 42 reliable assay of DNA methylation and can be effectively used to measure differential 43 methylation in mice. 44 Keywords: DNA methylation, epigenetics, microarray, cross-species comparison 45 3 bioRxiv preprint doi: https://doi.org/10.1101/194464; this version posted September 27, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 46 Introduction 47 There has been a surge in large-scale epigenetic studies in recent years. In particular, 48 epigenome-wide association studies (EWAS) of DNA methylation have shown 49 association with physiological traits [1,2], diseases [3-5], environmental exposures [6,7], 50 aging [8], and even socioeconomic [9] and emotional experiences [10]. The 51 development of robust and reliable methylation microarrays has been an important 52 driving force. In particular, the Illumina Human Methylation BeadChips have made it 53 both convenient and cost-effective to incorporate an epigenetic arm to large 54 epidemiological studies [11,12]. The latest version, the Illumina Infinium 55 MethylationEPIC BeadChip (EPIC), provides an efficient high throughput platform to 56 quantify methylation at 866,836 CpG sites on the human genome [13,14]. A remarkable 57 biological insight that has emerged from these array-based studies is the definition of 58 the methylation-based “epigenetic clock,” a biomarker of human age and aging (i.e., the 59 epigenetic clock) that is defined using specific probes represented on these arrays [8]. 60 Currently there is no equivalent microarray platform for model organisms and work in 61 experimental species have largely relied on high-throughput sequencing. For instance, 62 while the human DNA methylation age can be calculated from a few hundred probes on 63 the Illumina BeadChips, a similar effort in mice required a more extensive sequencing of 64 the mouse methylome [15]. However, CpG islands (CGIs) are largely conserved 65 between mice and humans and the two species share similar numbers of CGIs and 66 similar proportions of CGIs in promoter regions of genes [16]. Considering that these 67 CpGs and CGIs are highly conserved in gene regulatory regions, it is feasible that 4 bioRxiv preprint doi: https://doi.org/10.1101/194464; this version posted September 27, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 68 probes on the human microarrays that target these sites may have some application in 69 research using rodent models. This was previously evaluated for the two older versions 70 of the Illumina HumanMethylation BeadChips [17]. The work by Wong et al. 71 demonstrated that a subset of the probes targeting highly conserved sites provide 72 reliable measures of DNA methylation in mice, and could be feasibly used to evaluate 73 tissue specific methylation and in cancer related studies using the mouse as a model 74 system. 75 In the present work, we extend the conservation analysis to the EPIC platform, and 76 evaluate the capacity of these probes to detect differential methylation. We begin by 77 defining the conserved probes and the key features of the corresponding CpG sites in 78 the context of the larger mouse and human genome. We also compare the methylation 79 signal detected by the conserved probes with affinity-based methyl-CpG enriched DNA 80 sequence (MBD-seq) data from the same samples and evaluate if the conserved 81 probes are informative of age and strain differences in mice. 82 Materials and Methods 83 Defining Conserved EPIC probes 84 Sequences for the 866,836 CpG probes were obtained from Illumina 85 (http://www.illumina.com/). The probe sequences were aligned to the mouse genome 86 (mm10) using bowtie2 (version 2.2.6) with standard default parameters. A total of 87 34,981 probes aligned to the mouse genome of varying alignment quality. Conserved 88 probes were then defined based on quality of alignment. For this, we filtered out all 5 bioRxiv preprint doi: https://doi.org/10.1101/194464; this version posted September 27, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 89 sequences with a low mapping quality (MAPQ) of less than 60 (15,717 excluded) and 90 those that contain more than two non-matching base pairs (1,092). To retain only the 91 high quality probes, we further filtered probes based on confidence in DNA methylation 92 signal and based on this, 4,507 probes with detection p-values > 0.0001 were removed. 93 This generated a list of 13,665 high quality probes that are conserved sequences and 94 provide reliable methylation assays in mice (these are listed in Supplementary Data 95 S1). CpG island annotations [18] for the respective genome were downloaded from 96 UCSC Genome Browser (http://genome.ucsc.edu) and distribution of conserved probes 97 and positions of CGIs were plotted to the human (GRCh37) and mouse (mm10) 98 genomes using CIRCOS [19]. 99 For conserved sequences, there is high correspondence in functional and genomic 100 features between mouse and human genomes and we referred to the human probe 101 annotations provided by Illumina to define the location of conserved probes with respect 102 to gene features and CpG context (i.e., islands, shores, shelves) (Supplementary 103 Data S1). To evaluate if the conserved set is enriched in specific features relative to the 104 full background set, we performed a hypergeometric test using the phyper function in R. 105 Animals and sample preparation 106 Tissues samples were derived from mice that were part of an aging cohort maintained 107 at the University of Tennessee Health Science Center (PI: Robert W.
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