Literature DB >> 26317209

DNA-Methylation Patterns in Trisomy 21 Using Cells from Monozygotic Twins.

M Reza Sailani1, Federico A Santoni2, Audrey Letourneau1, Christelle Borel2, Periklis Makrythanasis2, Youssef Hibaoui3, Konstantin Popadin2, Ximena Bonilla2, Michel Guipponi2, Corinne Gehrig2, Anne Vannier2, Frederique Carre-Pigeon4, Anis Feki3, Dean Nizetic5, Stylianos E Antonarakis6.   

Abstract

DNA methylation is essential in mammalian development. We have hypothesized that methylation differences induced by trisomy 21 (T21) contribute to the phenotypic characteristics and heterogeneity in Down syndrome (DS). In order to determine the methylation differences in T21 without interference of the interindividual genomic variation, we have used fetal skin fibroblasts from monozygotic (MZ) twins discordant for T21. We also used skin fibroblasts from MZ twins concordant for T21, normal MZ twins without T21, and unrelated normal and T21 individuals. Reduced Representation Bisulfite Sequencing (RRBS) revealed 35 differentially methylated promoter regions (DMRs) (Absolute methylation differences = 25%, FDR < 0.001) in MZ twins discordant for T21 that have also been observed in comparison between unrelated normal and T21 individuals. The identified DMRs are enriched for genes involved in embryonic organ morphogenesis (FDR = 1.60 e -03) and include genes of the HOXB and HOXD clusters. These DMRs are maintained in iPS cells generated from this twin pair and are correlated with the gene expression changes. We have also observed an increase in DNA methylation level in the T21 methylome compared to the normal euploid methylome. This observation is concordant with the up regulation of DNA methyltransferase enzymes (DNMT3B and DNMT3L) and down regulation of DNA demethylation enzymes (TET2 and TET3) observed in the iPSC of the T21 versus normal twin. Altogether, the results of this study highlight the epigenetic effects of the extra chromosome 21 in T21 on loci outside of this chromosome that are relevant to DS associated phenotypes.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 26317209      PMCID: PMC4552626          DOI: 10.1371/journal.pone.0135555

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Genomic aneuploidy is a common cause of human genetic disorders that often results in dysregulation of gene expression patterns. A classic example of genomic aneuploidy is trisomy 21 (T21), which results to a collection of phenotypes known as Down syndrome (DS)[1]. Using monozygotic (MZ) twins discordant for T21, we have recently shown that the differential expression in T21 is organized in gene expression dysregulation domains (GEDDs) across the genome [2]. The DS associated phenotypes can be the result of the extra chromosomal material per se, or specific genes on chromosome 21. Some of the DS phenotypes (e.g., cognitive impairment) are consistently present in all DS individuals, while others show incomplete penetrance [1]. For the variable phenotypes with incomplete penetrance allele specific trisomy may be involved. In accordance with this hypothesis, we have reported the association of chromosome 21 SNPs and CNVs with an increased risk of congenital heart defect (CHD) in DS [3]. Alternatively, the variability of the phenotypes or the severity of the syndrome may be due to changes of the epigenetic landscape. Indeed, epigenetic alterations are known to contribute to human health and diseases [4-8]. Epigenetic modifications may also explain why MZ twins are not always phenotypically identical [9]. DNA methylation is among the best-studied epigenetic modifications thus far [8]. Potentially, DNA methylation could be involved in the response to gene dosage imbalances, for example in the case of aneuploidies. However, it is unclear if specific epigenetic events are needed for the development of DS phenotypes. There have been a few studies investigating the DNA methylation states in DS. In 2009, Zhang et al investigated chromosome 21 genes in DS and non-DS cells, and have found differences in promoter methylation of chromosome 21 genes [10]. Moreover, Kerkel et al., investigated DNA methylation profiling of 27,000 CpGs genome-wide using methylation arrays in peripheral blood leukocytes and T lymphocytes and reported gene specific abnormalities of CpG methylation in DS cases [11]. Although the number of CpGs investigated in this study (27,000 CpGs) is only a small fraction of CpGs, the results highlighted the importance of studying DNA methylation in aneuploid cases on a larger scale. Furthermore, Jin et al., investigated DNA methylation alterations associated with DS, in placenta villi of 11 DS cases and 6 normal controls [12], and identified genes with differential DNA methylation. However, it is not clear if these observations are specific to T21, or the results of the interindividual variability [13]. In the present study we hypothesized that there are epigenetic modifications in T21 that could potentially be linked to DS associated phenotypes. We applied Reduced Representation Bisulphite Sequencing (RRBS) to profile DNA methylation changes in a pair of rare MZ twins discordant for T21 [2,14] and two pairs of rare MZ twins concordant for trisomy 21, but discordant for CHD. We also studied two pairs of unaffected MZ twins without T21, as well as unrelated normal and T21 cases as controls. In addition, we have used iPS cells generated from MZ twins discordant for T21 to determine whether changes in DNA methylation in T21 are maintained during reprogramming. The results of this study identified epigenetic changes in genes involved in embryonic organ morphogenesis in MZ twins discordant for T21, and genes with potential involvement in heart development in T21 MZ twins discordant for CHD.

Material and Methods

Description of samples

Primary fetal fibroblasts from the MZ twins discordant for T21 were derived from skin tissue collected post mortem (Table 1, samples 1, 2, 3 and 4) [2,14]. Primary skin fibroblasts were also obtained from a pair of MZ twins concordant for T21, but discordant for CHD (VSD, ventricular septal defect in particular) (Table 1, samples 5 and 6). Informed consent was obtained for all these twin samples, and the Geneva University Ethics Committee approved the study. Additionally, we used amniocytes from a pair of MZ twins concordant for T21, but discordant for CHD (AVSD, Atrio Ventricular Septal Defect) (Table 1, samples 7 and 8). This twin set was obtained from Institut mère-enfant Alix de Champagne in France [15]. Moreover, primary fibroblasts from two pairs of healthy unaffected MZ twins (both normal euploid twins) have been used (Table 1, samples 9, 10, 11, and 12). Samples 9 and 10 have been obtained from the Geneva GenCord project [13], and samples 11 and 12 have been obtained from the TwinsUK resource (http://www.twinsuk.ac.uk) at the King's College London. The primary fibroblasts from unrelated T21 and normal individuals were taken from Prandini et al [16]. In addition to these samples, we also studied induced pluripotent stem cells (iPS) generated from the fetal skin fibroblasts of the MZ twins discordant for T21 [17] (Table 1, samples 15, 16 and 17). Table 1 shows the description of the samples used in this study.
Table 1

Description of samples used for DNA methylation analyses.

Sample setSample IDGenderDescriptionAge* Passage
MZ twins discordant for T21 (Replicate 1)Sample 1FemaleNormal primary fetal skin fibroblasts13 WGP13
MZ twins discordant for T21 (Replicate 1)Sample 2FemaleT21 primary fetal skin fibroblasts13 WGP13
MZ twins discordant for T21 (Replicate 2)Sample 3FemaleNormal primary fetal skin fibroblasts13 WGP13
MZ twins discordant for T21 (Replicate 2)Sample 4FemaleT21 primary fetal skin fibroblasts13 WGP13
T21 MZ twins discordant for VSDSample 5MaleT21 with VSD primary skin fibroblasts4 yearsP5
T21 MZ twins discordant for VSDSample 6MaleT21 without VSD primary skin fibroblasts4 yearsP5
T21 MZ twins discordant for AVSDSample 7MaleT21 with AVSD amniocytes17 WGNA
T21 MZ twins discordant for AVSDSample 8MaleT21 without AVSD amniocytes17 WGNA
Normal MZ twins pair 1Sample 9FemaleNormal primary fetal skin fibroblastsFetalP5
Normal MZ twins pair 1Sample 10MaleNormal primary fetal skin fibroblastsFetalP5
Normal MZ twins pair 2Sample 11FemaleNormal primary skin fibroblasts53 yearsP8
Normal MZ twins pair 2Sample 12FemaleNormal primary skin fibroblasts53 yearsP9
Unrelated normal and T21Sample 13FemaleT21 primary skin fibroblasts3 daysP14
Unrelated normal and T21Sample 14FemaleNormal primary skin fibroblasts2 daysP14
MZ twins discordant for T21 iPS cellsSample 15FemaleNormal iPS cells13 WGP10
MZ twins discordant for T21 iPS cellsSample 16FemaleT21 iPS cells13 WGP10
MZ twins discordant for T21 iPS cellsSample 17FemaleT21 iPS cells13 WGP10

*WG, Weeks of Gestation.

NA, Not Applicable

*WG, Weeks of Gestation. NA, Not Applicable

Cell culture

All the primary fibroblast cells were grown in DMEM GlutaMAX media (Life Technologies) enriched with 10% fetal bovine serum (FBS) (Life Technologies) and 1% penicillin/streptomycin/fungizone mix (Amimed, BioConcept) at 37°C in a 5% CO2 incubator. All the iPS cells were grown as previously described [17]. DNA extraction was performed using Qiagen DNeasy Blood and Tissue Kit from the primary skin fibroblast cells. Total RNA was extracted using the TRIzol reagent (Life Technologies) according to the manufacturer’s instructions. RNA quality was checked on the Agilent 2100 Bioanalyzer and quantity was measured on a Qubit instrument (Life Technologies).

RRBS library preparation and sequencing

We prepared RRBS libraries according to Gu H et al., with some modifications [18]. Briefly, 2 μg of genomic DNA was digested overnight at 37°C with 2 μl 20U/μl MspI and 5μl NEB4 (New England Biolabs Inc.) in a total reaction volume of 50 μl, followed by heat inactivation at 80°C for 20 minutes. Subsequently the end repair and A tailing were performed by adding 2 μl dNTP mix (10mM), 2 μl 5U/ μl Klenow fragment (New England Biolabs Inc.), and 4μl of NEB2 (New England Biolabs Inc.) in a total reaction volume of 40 μl. This reaction was incubated at 30°C for 20 minutes, followed by 20°C for 37 minutes. Heat inactivation was performed at 75°C for 20 minutes. The end-repaired and A tailed molecules were ligated to the methylated version of the Illumina adapters; ilAdap Methyl PE1: ACACTCTTTCCCTACACGACGCTCTTCCGATC*T (all C’s are methylated, * = phosphorothioate bond) and ilAdap Methyl PE2: GATCGGAAGAGCGGTTCAGCAGGAATGCCGA*G (all C’s are methylated, 5’ phosphate, * = phosphorothioate bond). The ligation was done using 1μl T4 DNA ligase (2,000 U/μl) (New England Biolabs Inc.), 2μl T4 ligase buffer (10X) (New England Biolabs Inc.), and 1μl methylated adapters (paired end adapters)(15 μM) in a total reaction volume of 20μl. The reaction was incubated in a thermocycler at 16°C overnight. The adapter ligated DNA was then purified by phenol extraction and ethanol precipitation and dissolved in 15 μl EB buffer. Size selection of the adapter ligated DNA fragments (170 bp to 350 bp) was done by electrophoresing the 15 μl ligation reaction in a 2.5% NuSieve GTG agarose gel (Lonza). We subsequently purified the DNA using a Qiagen Qiaquick Gel Extraction kit as described in the manufacturer’s instructions. We then used 20 μl of this purified DNA in the sodium bisulfite conversion step, which was performed using the QIAGEN Epitect Bisulfite Kit (Qiagen, Valencia CA, USA). The purified bisulfite treated DNA was then PCR amplified in a reaction containing 100 μl KAPA2G Robust DNA polymerase mixture (KAPA biosystems), 40μl bisulphite treated DNA, 0.5 mM ilPCR PE1 primer (AAT GAT ACG GCG ACC ACC GAG ATC TAC ACT CTT TCC CTA CAC GAC GCT CTT CCG ATC* T; * = phosphorothioate bond), 0.5 mM ilPCR PE2 primer (CAA GCA GAA GAC GGC ATA CGA GAT CGG TCT CGG CAT TCC TGC TGA ACC GCT CTT CCG ATC* T; * = phosphorothioate bond) in a total reaction volume of 200 μl. The PCR mixture were divided amongst eight PCR tubes, and were incubated at 95°C for 2 minutes, followed by 20 cycles of (95°C for 20 seconds and 65°C for 30 seconds and 72°C for 30 seconds), and finally 72°C for 7 minutes. The PCR products were pooled, and purified by adding 360 μl AMPure magnetic beads (Agencourt Bioscience, Beverly, MA). We quantified the purified product using the Qubit fluorometer (Invitrogen). We also checked the template size distribution of the library on Agilent Bioanalyzer (Agilent 2100 Bioanalyzer). We then diluted each library to 10 nM and proceeded to sequence each library (pair ended 100bp) in a single lane on the Illumina HiSeq 2000 according the manufacturer's instructions.

DNA methylation data processing

The quality of the reads were measured by FASTQC (version 0.10.1) program as implemented in the trime galore wrapper (http://www.bioinformatics.babraham.ac.uk). Low quality base calls were removed from the 3' end of the reads before trimming the adapter sequences. Our cut off for base quality control was Phred quality score of 20. Subsequently, Cutadapt detected and trimmed the adapter sequences from the 3’ end of reads. Bismark aligner [19] was used for mapping reads against the human genome hg19. For post data analyses purposes, we used an R library package methylKit [20] and custom scripts implemented in R and Python. We used the MethylKit package to calculate methylation percentages per each single CpG. Percent methylation values for CpG dinucleotides were calculated by dividing the number of methylated Cs by the total coverage on that base. CpGs with at least 20X read coverage and at least a Phred score threshold of 20 were retained for calling CpG methylation. We calculated DNA methylation state at single CpG sites and over genomic features such as promoters, CpG islands, and gene bodies (Exons and Introns).

DNA methylation level at single CpG sites and genomic regions

DNA methylation level was calculated for each sample both at single CpG sites and genomic regions. Genomic regions (GRCh37/hg19) include CpG islands, CpG shores (defined as 2000bp flanking regions on each side of the CpG island), promoters (defined as -2000bp, +1000bp around the TSS), and gene body (introns and exons), lamina associated domains (LADs), and regions between LAD domains (iLADs) [21]. For scoring DNA methylation in our analyses, each individual CpG was required to pass a minimum Phred base quality score of 20 and be covered at least by 20 reads. To score DNA methylation over a region, the region was required to contain at least three CpGs each covered by at least 20 reads.

RNA library preparation, sequencing and data processing

mRNA-seq data were prepared from 5μg of total RNA using the Illumina mRNA-Seq Sample Preparation kit (#RS-100-0801), according to the manufacturer’s instructions. One library per lane was sequenced on an Illumina HiSeq 2000 instrument (paired-end 100bp). Reads were uniquely mapped against the human genome (hg19) using the default parameters of the GEM aligner [22]. Quantile normalization was applied on the RPKM data (Reads Per Kilobase per Million). mRNA-Seq data for fibroblasts of MZ twins discordant for T21 (Samples 1, 2, 3 and 4) were taken from [2]. mRNA-seq data from iPS cells generated from MZ twins discordant for T21 fibroblasts (Samples 15, 16 and 17) were taken from [17].

Results

In this study we have used MZ twins to evaluate the role of the extra copy of chromosome 21 in epigenetic modifications related to T21. We applied RRBS to quantify DNA methylation at single CpG sites, and over genomic features. The RRBS method used in this study routinely achieved a bisulfite conversion rate greater than 99.8% for all of the samples studied, as calculated by methylKit [20]. A summary of mapped reads using the BisMark aligner against the human reference genome (hg19) is presented in S1 Table. Two technical replicates for the MZ twins discordant for T21 (replicate 1 and replicate 2) from the same culture, but with independent bisulfite conversion and library preparation were produced. The overall DNA methylation correlation between the two technical replicates was 0.90 for the normal twin (Samples 1 and 3 of Table 1) and 0.91 for T21 twin (Samples 2 and 4 of Table 1) (S1 Fig). Fig 1 shows the RRBS coverage of CpG sites in the MZ twins discordant for T21. A total of 2,598,760 CpGs (Phred base quality ≥ 20 and base read coverage ≥ 20) have been covered. That includes 70.7% of gene promoters, and 80.8% of CpG islands (Fig 1). Using the MZ twins discordant for T21 (samples 1, 2, 3 and 4 of Table 1) we observed a higher level of DNA methylation in the T21 twin compared to the normal twin. This has been observed both at the level of single CpG sites and the genomic features (Fig 2). Fig 2 shows the probability density distribution for methylation differences between the T21 and normal twin (Fig 2). The DNA methylation levels of promoters, introns, exons, CpG islands, CpG shores, LADs, and iLADs were determined, and the overall methylation levels were compared between MZ twins discordant for trisomy 21 using Mann–Whitney U test (Fig 2). There is a significant overall hyper-methylation for all the genomic features analyzed in T21 twin. However, the hyper-methylation of T21 twin compared to the normal twin is even more pronounced in promoters (p = 6.7e-48) and CpG islands (p = 1.9e-41) compared to other genomic regions (Fig 2).
Fig 1

CpGs Coverage of MZ-twins discordant for T21.

A) Distributions of covered CpGs (≥20X read coverage) by RRBS in promoters, exons, introns, and intergenic regions are shown in the pie chart. The blue bar in the histogram panel shows how many percentages of the genomic features are covered by RRBS. B) Distributions of covered CpGs (≥20X read coverage) by RRBS in CpG islands.

Fig 2

The overall DNA methylation level at single CpG resolution, and over genomic features.

The probability density distribution and the box-plot of DNA methylation shows differences between the T21 twin and the normal twin at the level of A) single CpG sites, B) promoters, C) CpG islands, D) Exons, E) Introns, F) LADs, and G) iLADs. The red line in the probability plot shows the probability distribution of T21 twin methylome subtracted from the normal twin methylome (T21—N). While, the blue line shows the probability distribution of the normal twin methylome subtracted from T21 twin methylome (N—T21). DNA hyper-methylation in T21 twin (T21 > Normal) is observed at the level of CpGs, and all the genomic features, but the effect is more pronounced in promoters and CpG islands.

CpGs Coverage of MZ-twins discordant for T21.

A) Distributions of covered CpGs (≥20X read coverage) by RRBS in promoters, exons, introns, and intergenic regions are shown in the pie chart. The blue bar in the histogram panel shows how many percentages of the genomic features are covered by RRBS. B) Distributions of covered CpGs (≥20X read coverage) by RRBS in CpG islands.

The overall DNA methylation level at single CpG resolution, and over genomic features.

The probability density distribution and the box-plot of DNA methylation shows differences between the T21 twin and the normal twin at the level of A) single CpG sites, B) promoters, C) CpG islands, D) Exons, E) Introns, F) LADs, and G) iLADs. The red line in the probability plot shows the probability distribution of T21 twin methylome subtracted from the normal twin methylome (T21—N). While, the blue line shows the probability distribution of the normal twin methylome subtracted from T21 twin methylome (N—T21). DNA hyper-methylation in T21 twin (T21 > Normal) is observed at the level of CpGs, and all the genomic features, but the effect is more pronounced in promoters and CpG islands. We next mapped DNA methylation profile to a gene model as described by Laurent et al 2010 [23]. This gene model includes all annotated genomic features in the vicinity of all transcribed genes in these twins. This gene model was used to compare the DNA methylation fold changes over the transcription start sites (TTS), gene bodies, transcription termination sites (TTS), and intergenic regions (Fig 3). For this analysis, promoters were defined as -10 kb to +1 kb of the TSS, TTS regions as -1 kb to +10 kb of the TTS, gene body regions as +1 kb from the TSS to -1 kb from the TTS, and intergenic regions consisted of regions not included in the three above mentioned categories [23]. The density of DNA methylation in each region was calculated as the percentage of methyl-cytosine over the total number of covered Cs in that region. We then calculated the fold change of DNA methylation in the T21 twin compared to the normal twin, and observed a higher DNA methylation level (≥ 1.5 fold change) in the gene promoters of T21 twin versus the normal twin (Fig 3). Consistently, the results of unrelated T21 and normal (samples 13 and 14 of Table 1) also showed hyper-methylation around the TSS in T21 compared to the unrelated normal individuals. In contrast normal MZ twins (samples 9 and 10 of Table 1) and MZ twins concordant for T21 (samples 5 and 6 of Table 1) did not show such difference (Fig 3C and 3D).
Fig 3

DNA methylation profile over a “Gene Model”.

DNA methylation fold change in A) Monozygotic twins discordant for T21, B) Unrelated T21 and normal cases, C) Normal MZ twins, D) T21 MZ twins. TSS and TTS represent transcription start site and transcription termination sites, respectively. The plot shows an increase in the level of DNA methylation around TSS in T21 twin compared to the normal twin.

DNA methylation profile over a “Gene Model”.

DNA methylation fold change in A) Monozygotic twins discordant for T21, B) Unrelated T21 and normal cases, C) Normal MZ twins, D) T21 MZ twins. TSS and TTS represent transcription start site and transcription termination sites, respectively. The plot shows an increase in the level of DNA methylation around TSS in T21 twin compared to the normal twin.

Differentially methylated regions (DMRs) in gene promoters

Since the RRBS method primarily enriches for promoter regions [24], we then focused in identifying differentially methylated regions (DMRs) in gene promoters in the MZ twins discordant for T21. Each promoter region was scored for being DMR using the Fisher's exact test. The P values were adjusted for multiple testing using the sliding linear model (SLIM) method that corrects P values to q-values as implemented in the methylKit package [20]. Promoters that met or exceeded a q-value of 0.001 and at least 25% absolute methylation differences were reported as being differentially methylated. Fig 4 illustrates the strategy that we have used in order to identify differentially methylated gene promoters in T21. DMRs in gene promoters from hg19 RefSeq genes (http://genome.ucsc.edu) were identified in each pair of twins and unrelated T21 and normal individuals. We have initially identified 462 gene promoters in MZ twins discordant for T21 that are differentially methylated (sample 1 and sample 3 versus sample 2 and sample 4). S2 Table represents the number of common DMRs observed in each sample set pair-wise comparisons (S2 Table). We have excluded any of the 462 DMRs identified in MZ twins discordant for T21 that have been also identified in at least one of the normal twins or T21 concordant twins. This was done in order to only keep those DMRs that are most likely to be due to the extra copy of chromosome 21. This filtering step resulted in 404 DMRs out of 462 to be uniquely present in MZ twins discordant for T21 (Fig 4). The majority of these DMRs are hypermethylated in T21 twins compared to the normal twin (353 gene promoters are hypermethylated and 51 gene promoters are hypomethylated).
Fig 4

Strategy used to define DMRs of gene promoters induced by the extra copy of chr21 in MZ twins discordant for T21.

DMRs are identified in each pair of twins, as well as unrelated normal and T21 cases. DMRs that are common among MZ twins discordant for T21, T21 MZ twins, and normal MZ twins have been excluded from the final candidate list. Subsequently, from this reduced list of DMRs, those that have been observed in unrelated T21 and normal individuals were selected as T21 induced candidate DMRs for further analyses. Each horizontal blue bar represents one pair of sample. The red vertical bars show DMRs. The numbers on the right side of each blue bar shows the number of identified DMRs in each pair of sample.

Strategy used to define DMRs of gene promoters induced by the extra copy of chr21 in MZ twins discordant for T21.

DMRs are identified in each pair of twins, as well as unrelated normal and T21 cases. DMRs that are common among MZ twins discordant for T21, T21 MZ twins, and normal MZ twins have been excluded from the final candidate list. Subsequently, from this reduced list of DMRs, those that have been observed in unrelated T21 and normal individuals were selected as T21 induced candidate DMRs for further analyses. Each horizontal blue bar represents one pair of sample. The red vertical bars show DMRs. The numbers on the right side of each blue bar shows the number of identified DMRs in each pair of sample. Since DMRs identified in MZ twins discordant for T21 are likely to be DMRs in unrelated T21 and normal individuals, we only included those DMRs that were also differentially methylated in unrelated T21 and normal cases, as well (Fig 4). This filtering step identified 35 common DMRs that were kept for further analyses. These DMRs mapped to 37 human Refseq genes (hg19, Table 2). We next performed gene ontology (GO) analyses [25,26] on the 37 genes for which a DMR was identified in their promoter regions. Table 3 shows the significant GO terms and the associated genes in each category. Interestingly, the significant GO terms are linked to embryonic organ morphogenesis and development (Table 3). All the genes in this category are hyper-methylated in the T21 compared to the normal twin. We observed that the majority of the genes in this category, such as HOXD3, HOXD10, HOXD12, HOXB5, and HOXB6 were also differentially methylated in iPS cells generated from primary fetal skin fibroblasts (samples 15, 16 and 17). Table 4 shows the absolute methylation differences, and the log2 ratio of fold change in gene expression for the significant GO term in MZ twins discordant for T21 fibroblast cells and MZ twins discordant for T21 iPS cells (Table 4). Moreover, a comparison of these results for genes involved in embryonic organ morphogenesis with previous studies of DNA methylation in DS is shown in S3 Table. Interestingly, the pattern of differentially methylated region is also observed for HOXD10, HOXB5, HOXB6 and HOXD12 across multiple studies in different tissues [11,12,27-29] (S3 Table). Additionally, we analyzed the enrichment of histone marks and transcription factor binding sites (TFBS) in 37 gene promoters for which a DMR was identified in MZ twins discordant for T21. Table 5 shows the significant enrichment signals for histone marks (ENCODE_Histone_Modifications_2015) and TFBS (ENCODE_TF_ChIP-seq_2015) [30] in ENCODE human cell lines based on the program Enrichr [31]. As shown in Table 5, this analysis confirms that the reported DMRs are targets of a common set of transcription factors and epigenetic regulators, including CTCF and EZH2 binding sites, and H3K27me3, H3K4me1 and H2AFZ chromatin marks.
Table 2

DMRs in MZ twin discordant for T21.

Chr.StartEndMeth (T21-N)* Gene nameGene description
chr1240162682401926868.33 RPL11 Ribosomal protein L11
chr111512326511512626533.29 BCAS2 Breast carcinoma amplified sequence 2
chr111512326511512626533.29 DENND2C DENN/MADD domain containing 2C
chr115590947915591247926.17 RXFP4 Relaxin/insulin-like family peptide receptor 4
chr2267805662678356626.11 OTOF Otoferlin
chr217696252917696552955.30 HOXD12 Homeobox D12
chr217697949117698249162.16 HOXD10 Homeobox D10
chr217702680417702980435.19 HOXD3 Homeobox D3
chr3183722125183725125-33.80 ABCC5 ATP-binding cassette, sub-family C
chr319594138219594438225.26 SLC51A Solute carrier family 51
chr5795508987955389849.96 SERINC5 Serine incorporator 5
chr514079853614080153625.12 PCDHGA1 Protocadherin gamma subfamily A
chr5179498118179501118-26.77 RNF130 Ring finger protein 130
chr712914031912914331943.34 SMKR1 Small lysine-rich protein 1
chr714893474114893774147.16 ZNF212 Zinc finger protein 212
chr810438174210438474231.30 CTHRC1 Collagen triple helix repeat containing 1
chr93590418835907188-25.15 HRCT1 Histidine rich carboxyl terminus 1
chr9131682561131685561-39.51 PHYHD1 Phytanoyl-coa dioxygenase domain 1
chr913240344813240644840.11 ASB6 Ankyrin repeat and SOCS box containing 6
chr913388250313388550330.65 LAMC3 Laminin, gamma 3
chr1010002700710003000741.49 LOXL4 Lysyl oxidase-like 4
chr11175649631756796341.50 USH1C Usher syndrome 1C
chr15744640867446708638.36 ISLR Immunoglobulin superfamily leucine-rich
chr15914714099147440939.87 HDDC3 HD domain containing 3
chr16682664026826940233.39 ESRP2 Epithelial splicing regulatory protein 2
chr16731242477312724731.28 HCCAT5 Hepatocellular carcinoma transcript 5
chr16755279267553092652.13 CHST6 Carbohydrate
chr178868029887102925.36 PIK3R5 Phosphoinositide-3-kinase
chr17466713194667431945.27 HOXB5 Homeobox B5
chr17466713194667431945.27 HOXB6 Homeobox B6
chr194866780486978044.22 PLIN3 Perilipin 3
chr19362470433625004327.12 HSPB6 Heat shock protein B6
chr19468482504685125025.66 PPP5C Protein phosphatase 5, catalytic subunit
chr19555852205558822030.81 EPS8L1 EPS8-like 1
chr203022369030226690-26.72 COX4I2 Cytochrome c oxidase subunit IV isoform 2
chr20452791004528210025.21 SLC13A3 Solute carrier family 13
chr21463389494634194955.20 ITGB2 Integrin, beta 2

*Meth (T21 –N) represents the percent methylation difference between T21 twin and normal twin. The positive sign means T21 twin is more methylated than the Normal twin, and the negative sign means Normal twin is more methylated than T21 twin.

Table 3

GO terms associated with DMRs identified in MZ twins discordant for T21.

Biological ProcessGene NameGene Description P FDR
Embryonic organ morphogenesis HOXD3 Homeobox D36.52E-061.60E-03
CTHRC1 Collagen triple helix repeat containing 1
USH1C Usher syndrome1C
HOXB5 Homeobox B5
HOXB6 Homeobox B6
HOXD10 Homeobox D10
Embryonic skeletal system morphogenesis HOXD3 Homeobox D32.79E-053.40E-03
HOXB5 Homeobox B5
HOXB6 Homeobox B6
HOXD10 Homeobox D10
Embryonic morphogenesis HOXD12 Homeobox D127.85E-053.40E-03
HOXD3 Homeobox D3
HOXB5 Homeobox B5
HOXB6 Homeobox B6
HOXD10 Homeobox D10
CTHRC1 Collagen triple helix repeat containing 1
USH1C Usher syndrome1C

P, nominal p-value.

FDR, False Discovery Rate- Benjamini–Hochberg.

Table 4

DNA methylation differences and gene expression fold changes in fibroblasts and iPSC of MZ twins discordant for T21; the genes listed are from Table 3.

MZ twins discordant for T21 fibroblast cellsMZ twins discordant for T21 iPS cells
Gene nameMethylation difference* (T21 twin-Normal twin)Gene expression difference Log2 (T21/Normal)Methylation difference* (T21 iPS–Normal iPS)Gene expression difference Log2 (T21 iPS /Normal iPS)
HOXD3 35.2-0.8036.4-5.7
HOXD10 62.16-2.84-6.8-1.02
HOXB5 45.3-0.3259-7
HOXB6 45.3-1.8559-5
CTHRC1 31.3-0.30-53.40.43
USH1C 41.500.0-50.4
HOXD12 60.583.1277.92-0.03
Correlation -0.86-0.56

* Methylation difference is the percent methylation differences between fibroblast cells of T21 twin and Normal twin (column 2) and between iPS cells of T21 twin and Normal twin (column 4).

Correlation is the Pearson correlation between DNA methylation differences in column 2 and Log2 ratio of gene expression differences in column 3, and between DNA methylation differences in column 4 and Log2 ratio of gene expression differences in column 5.

Table 5

Histone modification and TFBS enrichment analyses of DMRs associated with T21.

ENCODE Histone Modification gene-set library (Human)
Histone Mark P FDR Genes
H3K27me39E-050.01 CHST6;ESRP2;LAMC3;USH1C;EPS8L1;HOXD3;HOXD10;RNF130;ZNF212;PIK3R5
H3K4me15E-040.03 ISLR;CHST6;HSPB6;LAMC3;PHYHD1;ITGB2;PCDHGA1;HOXD10;ZNF212
H2AFZ2E-030.06 DENND2C;PPP5C;ISLR;PHYHD1;RPL11;PCDHGA1;BCAS2;ZNF212
ENCODE TF ChIP-seq gene-set library (Human)
TF P FDR Genes
CTCF2E-040.1 PPP5C;RPL11;ASB6;HOXD12;HDDC3;ZNF212;HOXB5;CTHRC1
EZH21E-030.1 PPP5C;CHST6;ESRP2;COX4I2;OTOF;EPS8L1;LOXL4;HDDC3;PIK3R5

P, nominal p-value.

FDR, False Discovery Rate- Benjamini–Hochberg.

*Meth (T21 –N) represents the percent methylation difference between T21 twin and normal twin. The positive sign means T21 twin is more methylated than the Normal twin, and the negative sign means Normal twin is more methylated than T21 twin. P, nominal p-value. FDR, False Discovery Rate- Benjamini–Hochberg. * Methylation difference is the percent methylation differences between fibroblast cells of T21 twin and Normal twin (column 2) and between iPS cells of T21 twin and Normal twin (column 4). Correlation is the Pearson correlation between DNA methylation differences in column 2 and Log2 ratio of gene expression differences in column 3, and between DNA methylation differences in column 4 and Log2 ratio of gene expression differences in column 5. P, nominal p-value. FDR, False Discovery Rate- Benjamini–Hochberg. Furthermore, since the majority of the DMRs detected in the MZ twin discordant for T21 are hyper-methylated in T21, we subsequently evaluated the genes that are known to be directly involved in DNA methylation and de-methylation processes. The addition of methyl group to CpGs is controlled at several different levels and is carried out by a family of enzymes called DNA methyltransferases (DNMTs) (DNMT2, DNMT3L, DNMT3a and DNMT3b) [32]. On the contrary, active DNA demethylation is carried out by ten-eleven translocation (TET) enzyme-mediated oxidation (TET1, TET2 and TET3) [33]. Based on RNAseq data available from the iPS cells generated from the MZ twins discordant for T21 (55), we have observed an over-expression of DNA methyltransferase enzymes (DNMT3B and DNMT3L) and down regulation of TET2 and TET3 involved in DNA demethylation processes in T21 iPS cells compared to the normal twin iPS cells (Fig 5). It is of note that DNMT3L maps on chromosome 21, and its expression level in the T21 iPS cells is three fold greater than in the normal iPS cells. However, we did not observe expression changes of these genes in the skin fibroblast cell cultures. This may suggest that these epigenetic changes potentially happen in early embryonic stages [34].
Fig 5

Gene expression fold changes of enzymes involved in DNA methylation.

The log2 ratio of fold change is based on the average RPKM values of four normal twin iPS cell replicates and the average RPKM values of three T21 twin iPS cell replicates.

Gene expression fold changes of enzymes involved in DNA methylation.

The log2 ratio of fold change is based on the average RPKM values of four normal twin iPS cell replicates and the average RPKM values of three T21 twin iPS cell replicates.

Methylation differences in T21 MZ twins discordant for CHD

We had also the opportunity to study two sets of T21 MZ twins discordant for CHD, and thus investigated DMRs that could potentially be linked to this common but heterogeneous congenital phenotype in DS. The first twin set was discordant for VSD (Samples 5 and 6) (Table 1), and the second set for AVSD (Samples 7 and 8) (Table 1). AVSD is the most common (43% of CHD cases in DS), and VSD is the second common cardiac defect in DS (32% of CHD cases in DS) [35]. Although genomic variation on chromosome 21 has been shown to modify the risk of CHD [3], in the case of MZ twins the genome is similar. Therefore, CHD may be the result of epigenetic alterations in concert with T21, or a stochastic event. We have identified 197 DMRs (25% methylation differences and q-value less than 0.001) in MZ twins discordant for VSD (Samples 5 and 6), and 88 DMRs in MZ twins discordant for AVSD (Samples 7 and 8), including 13 common DMRs between two sets. Table 6 shows the common DMRs observed in both twin sets and their association with different heart phenotypes based on previous studies [36-43]. However, the direction of DNA methylation is different for some of the gene promoters (CBFA2T3, EPHA8, LY9, SLC9A3R2) between VSD and AVSD (Table 6). This may suggest that the up or down regulation of these genes can lead to different heart phenotypes. The GO term analyses performed on genes harboring DMRs in MZ-twins discordant for AVSD (Samples 7 and 8), show an enrichment for endocardial cushion morphogenesis genes (adjusted P value 0.0091) and genes involved in metanephric nephron tube formation (adjusted P value 0.008) (Table 7). Additionally, we observed enrichment for genes involved in pyridine-containing compound metabolic process (adjusted P value 0.033) in MZ twins discordant for VSD (Samples 5 and 6) (Table 7). Furthermore, the top scores for TFBS enrichment analyses for DMRs in T21 twins discordant for AVSD highlighted EP300, E2F6, SMC3 and CEBPB binding sites, and for T21 twins discordant for VSD highlighted POLR2A (polymerase (RNA) II polypeptide A), CTCF and EP300 (Tables 8 and 9). Moreover, the top scores for histone modification marks enrichment analyses confirms the enrichment of marks associated with active enhancers such as H3K4me1 and H3K27ac in DMRs associated with both AVSD and VSD (Tables 8 and 9).
Table 6

Common DMRs observed in the two sets of T21 MZ twins discordant for AVSD and VSD.

GeneGene descriptionAVSD TwinsVSD TwinsLog2FCRef.
Meth. differencesMeth. differences
PCDHGB1 Protocadherin gamma subfamily B, 1-44.44-43.88-1.59-
PFKFB2 6-phosphofructo-2-kinase29.6792.29-1.6-
TRPC3 Transient receptor potential cationchannel-26.14-43.45-0.86Ref. (26,33)
WDR27 WD repeat domain 27-29.23-27.91-1-
YOD1 YOD1 deubiquitinase29.6692.28-1.4Ref. (28)
CBFA2T3 Core-binding factor, runt domain26.46-26.060.09Ref. (27)
CSRNP2 Cysteine-serine-rich nuclear protein 226.2155.58-1.5-
DIP2C DIP2 disco-interacting protein 2 homolog C-34.88-25.81-1.32-
EPHA8 EPH receptor A830.86-33.741-
LY9 Lymphocyte antigen 9-55.734.54NA-
NFATC1 Nuclear factor of activated T-cells-30.08-25.81-1Ref. (29,30)
SLC9A3R2 Solute carrier family 9-38.7832.26-1.8Ref. (31)
TNNT3 Troponin T type 3-36.11-59.850Ref. (32)

Methylation differences show the DNA methylation percent difference between normal twin and twin with cardiac defect. Log2FC shows log2 fold change of RPKM value of gene expression in T21 normal twin over T21 twin with VSD. Gene expression data for T21 twins discordant for AVSD is not available. NA, Not available.

Table 7

GO terms associated with DMRs identified in T21 MZ twins discordant for CHD.

T21 MZ twins discordant for AVSD
Biological process Gene Gene description P FDR
Endocardial cushion morphogenesis ENG Endoglin4.08E-059.00E-03
TBX2 T-box 2
RBPJ Recombination signal binding protein
SOX9 SRY box 9
Metanephric nephron tubule formation PAX2 Paired box 28.01E-068.00E-03
SOX9 SRY box 9
PAX8 Paired box 8
T21 MZ twins discordant for AVSD
Pyridine-containing compound metabolic process PNPO Pyridoxamine 5'-phosphate oxidase4.64E-053.30E-02
GCK Glucokinase
NUDT1 Nudix
NMRK2 Nicotinamide riboside kinase 2
NADK NAD kinase
LDHB Lactate dehydrogenase B

P, nominal p-value.

FDR-BH, False Discovery Rate- Benjamini–Hochberg.

Table 8

Histone modification and TFBS enrichment analyses of DMRs associated with VSD.

ENCODE Histone modification gene-set library (Human)
Histone Mark P FDR Genes
H2AFZ3.2E-081.3E-05 PXT1;AGPAT6;HDAC5;ITGB5;CCDC149;VPS4A;NAT10;NOD1;ASH2L;CKMT2;
SEC14L1;FLAD1;WDR93;NDUFV3;IP6K1;ZNF687;ZBED3;CDKL3;TRPC3;
SETDB1;PCDHGA1;YOD1;ISG15;CORO2A;ESPL1;ZSCAN23;L1TD1;CDK12;
NIT1;SEC24D;HPD;LINC00346
H3K4me13.0E-053.1E-03 IFITM3;PXT1;CCDC149;SLC2A5;AQP3;PPCDC;CKMT2;KCTD20;C14ORF2;
PPP6R2;KIAA0226L;CD14;SMYD3;NAE1;DIP2B;ZNF589;CDKL3;ACBD4;
LYSMD1;DGKZ;GCFC2;SLC6A9;LUC7L3;STEAP1;HPD;CAPS2;
H3K27ac4.1E-053.4E-03 CCDC101;PXT1;AGPAT6;NDUFA10;ISG20L2;ASH2L;C1ORF174;PHKG1;KCTD20;
STK36;DGCR8;NDUFV3;ZNF687;ZBED3;GUSBP1;C8ORF59;SETDB1;ATAD5;
LRBA;IFNGR2;LYSMD1;ISG15;SMU1;NBR2;NIF3L1;CFDP1;NHP2L1;ESPL1;
NCL;MITD1;NAA16;ZNF414;CDK12;NIT1;STEAP1;C22ORF15;CAPS2;LINC00346
ENCODE TF ChIP-seq gene-set library (Human)
TF P FDR Genes
POLR2A7.7E-083.1E-05 CSRNP2;FAF1;C15ORF61;ASH2L;ARID4B;C1ORF174;AQP3;PPCDC;UBL5;ALDH2;
C14ORF2;FUNDC1;PPP6R2;DGCR8;ZNF687;NUDT12;TMPO;WDR38;CDKL3;
GUSBP1;C8ORF59;TBCCD1;IFNGR2;TET2;YOD1;NIF3L1;NHP2L1;ESPL1;THRAP3;
NCL;LUC7L3;ZSCAN23;HPRT1;STEAP1;HPD;PXT1;AGPAT6;TSSC1;VPS4A;NOD1;
C17ORF51;OAZ2;SEC14L1;KCTD20;STK36;PNPO;SMYD3;NAE1;NDUFV3;
ZNF589;IP6K1;NADK;TBC1D16;GINS1;ACBD4;CCDC12;ATAD5;LRBA;SGTA;
LYSMD1;ISG15;SMU1;NUDT9;NBR2;STK24;CAPZA2;GNB4;MITD1;NAA16;
ISG15;SMU1;NUDT9;NBR2;STK24;CAPZA2;GNB4;MITD1;NAA16;SEC24D;
FERMT3;LINC00346
EP3001.1E-069.3E-05 CSRNP2;FAF1;NDUFA10;C15ORF61;RPL10A;UBL5;ALDH2;FLAD1;FUNDC1;
PPP6R2;ZNF687;TMPO;CDKL3;GUSBP1;IQCD;GCFC2;NIF3L1;CFDP1;FAM161A;
NHP2L1;ESPL1;THRAP3;NCL;LGALS12;TLCD1;STEAP1;HPD;CCDC101;PXT1;
TSSC1;NOD1;MTMR6;SOCS2;SEC14L1;KCTD20;STK36;SMYD3;NDUFV3;
ZNF589;IP6K1;NADK;GINS1;SETDB1;CCDC12;ATAD5;LRBA;LYSMD1;SMU1;
NBR2;TCEA2;MITD1;ZNF414;HIST1H4D;LINC00346
CTCF1.3E-069.4E-05 BCAR3;CCDC101;AGPAT6;TSSC1;CCDC149;FAF1;VPS4A;NAT10;NOD1;
RPL10A;AQP3;CX3CL1;MTMR6;SOCS2;KCNT1;SEC14L1;ALDH2;PHKG1;
C14ORF2;FUNDC1;SMYD3;NAE1;DIP2B;ZNF589;WDR38;GUSBP1;ACBD4;
SETDB1;SGTA;PCDHGA1;CORO2A;NUDT9;NBR2;ESPL1;CAPZA2;TLCD1;
STEAP1;HPD;HIST1H4D;LINC00346

P, nominal p-value.

FDR, False Discovery Rate- Benjamini–Hochberg.

Table 9

Histone modification and TFBS enrichment analyses of DMRs associated with AVSD.

ENCODE Histone modification gene-set library (Human)
Histone Mark P FDR Genes
H3K4me11E-050.006 GABRB3;FAM49A;PLA2G12B;TPM3;KRT8;TMC6;TMPRSS13;ROCK1P1;
RND1;HAUS1;LSM12;SPATA17;CCDC80;SUMO2;SLC26A9;MIR190B;ENG
H3K27me36E-040.052 GABRB3;FAM49A;PLA2G12B;TPM3;KRT8;TMC6;TMPRSS13;ROCK1P1;
C9ORF129;F8;DLG3;PTCHD3;MIR190B;BCAS1;CES1
ENCODE TF ChIP-seq gene-set library (Human)
EP3002E-050.018 H2AFB1;CSRNP2;LUZP1;CSTF3;ATP5A1;GPATCH2;RPL36A;RND1;PIM2;
ZNF585B;SLC35A2;MED1;TTC37;PTGIR;TIPIN;F8A1;HIST1H4K;KRT8;
PDE4DIP;YOD1;MARCH8;TMC6;HAUS1;LENG1;LATS1;PAN2;CDC20B;PKIB;
SPATA17;GSTA4;EBPL
E2F62E-040.049 TTC37;TIPIN;CSRNP2;ATP5A1;MARCH8;CLK2;HAUS1;LENG1;LATS1;PAN2;
CDC20B
SMC31E-040.049 SLC35A2;TTC37;CSRNP2;RPL36A;KRT8;MIR449C;RND1;PKIB;SPATA17;
GSTA4;ARSK; SERINC1;PIM2;LRRC4C;ZNF585B;BCAS1;CES1
CEBPB2E-040.049 MED1;CSRNP2;LUZP1;RPL36A;YOD1;MAGT1;CMAHP;RND1;LENG1; LATS1;
CDC20B;F8;LSM12;GSTA4;ARSK;SUMO2;EBPL;PIM2;ZNF585B;CES1

P, nominal p-value.

FDR, False Discovery Rate- Benjamini–Hochberg.

Methylation differences show the DNA methylation percent difference between normal twin and twin with cardiac defect. Log2FC shows log2 fold change of RPKM value of gene expression in T21 normal twin over T21 twin with VSD. Gene expression data for T21 twins discordant for AVSD is not available. NA, Not available. P, nominal p-value. FDR-BH, False Discovery Rate- Benjamini–Hochberg. P, nominal p-value. FDR, False Discovery Rate- Benjamini–Hochberg. P, nominal p-value. FDR, False Discovery Rate- Benjamini–Hochberg.

Discussion

DNA methylation analysis of fibroblasts from a rare pair of MZ twin discordant for T21, combined with normal MZ twins and T21 MZ twins as controls, revealed differences in promoter regions of genes involved in embryonic organ morphogenesis such as HOXB5, HOXB6, HOXD3, HOXD10 and HOXD12 in T21. Although the majority of these loci are hyper-methylated in the T21 compared to the normal twin, there is no enrichment for chromosome 21 genes. This highlights the point that the effect of the extra copy of chromosome 21 is not restricted to genes located on chromosome 21, and can modify the epigenetic status of loci located in the rest of the genome [2]. The fact that these gene regions are also differentially methylated in iPS cells suggests that these epigenetic marks are not tissue specific and are stably maintained. HOX genes, transcription factors of the homeobox superfamily, are major regulators of animal development and regulate many biological processes including embryonic morphogenesis and differentiation [44,45]. Aberrant expression of HOX genes is associated with several abnormalities. For instance, altered expression of Hoxb6 in mice has been associated with craniofacial abnormalities [46]. HOXB5 encodes a protein that functions as a sequence-specific transcription factor that is mainly involved in lung and gut development [47]. Altered expression of HOXB5 is linked to AML, bronchopulmonary sequestration and congenital cystic adenomatoid malformation tissue [48,49]. Also, the HOXD gene cluster has been associated with severe genital and limb abnormalities [50-52]. Moreover, in accordance with the observation that HOXB and HOXD gene clusters are down-regulated in T21, Billingsley C et al reported this observation when comparing 13 Ts65Dn (DS mouse model) and 11 euploid mouse embryos at 13.5 days gestation (E13.5) [53]. Altogether, these results indicate that dysregulation of HOX genes mediated by DNA methylation modification may play an important role in DS associated phenotypes. Another observation in the DNA methylation analyses of MZ twins discordant for T21 is the presence of a higher level of DNA methylation in the genome of the T21 twin compared to the normal twin, both in iPSC and fibroblasts. This observation was also reported in unrelated T21 and normal individuals [12]. When the genome was dissected in different genomic features, the DNA hyper-methylation was even more pronounced in promoters and CpG islands. Therefore, it suggests that the presence of the extra copy of chromosome 21 in DS cases is associated with an increase in the overall genome methylation in T21. The hyper-methylation state of the T21 methylome versus the normal methylome in iPSC is interestingly associated with the up-regulation of DNA methyl-transferase genes (DNMT3B and DNMT3L), and down-regulation of DNA de-methylation genes (TET2 and TET3) in T21 twin. However, it is still unclear if the presence of the extra copy of chromosome 21 per se, or specific gene(s) located on chromosome 21 is (are) leading this effect. It is of note that DNMT3L, a DNA methyltransferase regulator, maps on chromosome 21. Since DNA methylation patterns are established during early embryonic development [34], any changes in the methyltransferases activity can lead to disturbed methylation patterns in the cells [54]. DNMT3L increases the activity of DNMT3a and DNMT3b [54] that are the main enzymes required for De Novo DNA methylation and are extremely similar in structure and function [55,56]. However, it seems that DNMT3b is needed during early development, while DNMT3a is required for normal cellular differentiation [57]. Moreover, Baubec et al recently has shown the selective binding of DNMT3B to the bodies of transcribed genes, while excluded from active promoters and enhancers [58]. In accordance with the 3.1 fold change increase in the expression level of DNMT3L in T21 twin iPSC, we observed 3.2 fold change increase also in the expression level of DNMT3b in T21 iPSC compared to normal twin iPSC (Fig 5). These results suggest that the overexpression of specific genes on chromosome 21 (i.e., DNMT3L) (rather than the extra-material per se) leads to the hypermethylation of the genome in T21. However, further experiments are required to explore the association of DNMT3L and DNA methylation in the context of T21. Moreover, we have observed enrichment for histone marks H3K27me3 and H3K4me1, and for CTCF and EZH2 binding sites in DMRs related to DS (Table 5). CTCF is a master regulator that plays a central role in multiple complex genomic processes, including transcription, imprinting, and chromatin interactions [59]. Recently, Wang et al reported a strong link between DNA methylation and the global occupancy patterns of CTCF. They have shown that the majority of CTCF binding sites are un-methylated and confirming an inverse relationship between methylation and CTCF occupancy [59]. EZH2 is also involved in maintaining the transcriptional repressive state of genes via H3K27me3 (repressive mark associated with constitutive heterochromatin), leading to transcriptional repression of the affected target gene. EZH2 also serves as a recruiting platform for DNA methyltransferase enzymes, thereby linking two epigenetic repression systems [60]. The fact that there is an enrichment for binding sites of CTCF and EZH2 which overlaps with the location of repressive histone marks H3K27me3 and H3K4me1 in DMRs associated with MZ twins discordant for T21, suggests that the altered methylation level in DNA sequence can potentially reflect the altered epigenetic architecture of chromatin structure. Whether DNA methylation alteration initiate the cascade of changes in the epigenetic architecture, or it is a result of changes in other epigenetic factors is not well known. Furthermore, CHD is one of the most heterogeneous variable phenotypes in DS, and is present in 40% of the cases [35]. Recently, whole exome sequencing in a population of CHD cases pointed to the importance of epigenetic alterations in the pathogenicity of CHD in the general population [61]. Moreover, Serra-Juhé et al 2015 investigated the global methylation profile of fetal heart DNA in comparison to blood DNA from control subjects [62]. This study revealed a significant enrichment of differential methylation at genes related to muscle contraction and cardiomyopathies in the developing heart DNA in both isolated and syndromic heart malformations [62]. Since two sets of MZ twins in this study are concordant for T21, but discordant for CHD, they provide a unique opportunity to investigate the association of DNA methylation with the development of CHD in the context of T21. Interestingly, T21 MZ twins discordant for AVSD show enrichment for endocardial cushion morphogenesis genes (adjusted P-value 0.0091). This GO term includes ENG, TBX2, RBPJ, and SOX9 (Table 7) that all are involved in heart development [63-65]. The MZ twins discordant for VSD show enrichment for the genes involved in pyridine-containing compound metabolic process (adjusted P-value 0.033) (Table 7). However, it is not known whether the pyridine-containing compounds are involved in heart development. Additionally, the ENCODE transcription factor binding enrichment analyses show a significant enrichment for binding sites of EP300 and its paralog CREBBP that are ubiquitously expressed transcriptional co-activators and histone acetyl transferases. Both of these factors are essential for normal cardiac and neural development [66]. On the contrary, E2F6 and CTCF binding sites that are also significantly enriched in DMRs associated with T21 twins discordant for AVSD, are transcription repressors [67]. E2F6 interacts with Dnmt3b and is required for binding of DNMT3B at CpG-islands [68], however it is not known that this interaction leads to the establishment or to the maintenance of DNA methylation. In conclusion, the study of DNA methylation differences in MZ twins discordant for T21 revealed epigenetic alterations of gene promoters that are involved in embryonic organ morphogenesis and might be relevant to DS phenotypes. These DMRs are also targets of a common set of transcription factors and epigenetic regulators. In addition, we have observed an overall hypermethylation of DS genome compared to euploid normal genome, particularly in promoters and CpG islands. Moreover, the study of DNA methylation differences in T21 twins discordant for CHD highlighted epigenetic alterations of gene promoters that might be linked to the heart development. Furthermore, there is a significant enrichment for binding sites of EP300 and CREBBP that are important for heart development in both twins discordant for AVSD, and discordant for VSD. Altogether, the results of this study highlight the epigenetic effects of the extra chromosome 21 in T21 on loci outside of this chromosome that are relevant to DS associated phenotypes.

Correlation heatmap of two technical replicates for the MZ twins discordant for T21 methylome (Samples 1, 2, 3 and 4).

For the normal twin (Samples 1 and 3) the correlation is 0.90, and for the T21 twin (Samples 2 and 4) the correlation is 0.91. The colors represent the local densities at each point in the scatterplot. The red line is linear regression fit and the blue line is loess fit. (TIFF) Click here for additional data file.

Samples used for DNA methylation analyses and their sequencing information.

Total reads, show the raw number of sequenced reads in million (M) obtained for each sample. Mapped, shows the number of reads uniquely mapped against the human genome hg19 in million (M). (DOCX) Click here for additional data file.

The common number of DMRs in each sample set pair-wise comparison.

(DOCX) Click here for additional data file.

Overlapping DMRs of table 2 with the previous studies of DNA methylation in DS.

*Fetal Liver Mononuclear Cells. DS, Down syndrome. N, normal. M, Million. K, Thousands. (DOCX) Click here for additional data file.
  68 in total

1.  Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling.

Authors:  Hongcang Gu; Zachary D Smith; Christoph Bock; Patrick Boyle; Andreas Gnirke; Alexander Meissner
Journal:  Nat Protoc       Date:  2011-03-18       Impact factor: 13.491

2.  Dnmt3b recruitment through E2F6 transcriptional repressor mediates germ-line gene silencing in murine somatic tissues.

Authors:  Guillaume Velasco; Florent Hubé; Jérôme Rollin; Damien Neuillet; Cathy Philippe; Haniaa Bouzinba-Segard; Angélique Galvani; Evani Viegas-Péquignot; Claire Francastel
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-03       Impact factor: 11.205

3.  Altered DNA methylation in leukocytes with trisomy 21.

Authors:  Kristi Kerkel; Nicole Schupf; Kota Hatta; Deborah Pang; Martha Salas; Alexander Kratz; Mark Minden; Vundavalli Murty; Warren B Zigman; Richard P Mayeux; Edmund C Jenkins; Ali Torkamani; Nicholas J Schork; Wayne Silverman; B Anne Croy; Benjamin Tycko
Journal:  PLoS Genet       Date:  2010-11-18       Impact factor: 5.917

Review 4.  A twin approach to unraveling epigenetics.

Authors:  Jordana T Bell; Tim D Spector
Journal:  Trends Genet       Date:  2011-01-21       Impact factor: 11.639

5.  Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications.

Authors:  Felix Krueger; Simon R Andrews
Journal:  Bioinformatics       Date:  2011-04-14       Impact factor: 6.937

6.  HOXB5 expression in oral squamous cell carcinoma.

Authors:  Renata Tucci; Marcia Sampaio Campos; Luciana Fasanella Matizonkas-Antonio; Marcelo Durazzo; Décio dos Santos Pinto Junior; Fabio Daumas Nunes
Journal:  J Appl Oral Sci       Date:  2011-04       Impact factor: 2.698

7.  WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013.

Authors:  Jing Wang; Dexter Duncan; Zhiao Shi; Bing Zhang
Journal:  Nucleic Acids Res       Date:  2013-05-23       Impact factor: 16.971

8.  Global DNA hypermethylation in down syndrome placenta.

Authors:  Shengnan Jin; Yew Kok Lee; Yen Ching Lim; Zejun Zheng; Xueqin Michelle Lin; Desmond P Y Ng; Joanna D Holbrook; Hai Yang Law; Kenneth Y C Kwek; George S H Yeo; Chunming Ding
Journal:  PLoS Genet       Date:  2013-06-06       Impact factor: 5.917

9.  Passive and active DNA methylation and the interplay with genetic variation in gene regulation.

Authors:  Maria Gutierrez-Arcelus; Tuuli Lappalainen; Stephen B Montgomery; Alfonso Buil; Halit Ongen; Alisa Yurovsky; Julien Bryois; Thomas Giger; Luciana Romano; Alexandra Planchon; Emilie Falconnet; Deborah Bielser; Maryline Gagnebin; Ismael Padioleau; Christelle Borel; Audrey Letourneau; Periklis Makrythanasis; Michel Guipponi; Corinne Gehrig; Stylianos E Antonarakis; Emmanouil T Dermitzakis
Journal:  Elife       Date:  2013-06-04       Impact factor: 8.140

10.  De novo mutations in histone-modifying genes in congenital heart disease.

Authors:  Samir Zaidi; Murim Choi; Hiroko Wakimoto; Lijiang Ma; Jianming Jiang; John D Overton; Angela Romano-Adesman; Robert D Bjornson; Roger E Breitbart; Kerry K Brown; Nicholas J Carriero; Yee Him Cheung; John Deanfield; Steve DePalma; Khalid A Fakhro; Joseph Glessner; Hakon Hakonarson; Michael J Italia; Jonathan R Kaltman; Juan Kaski; Richard Kim; Jennie K Kline; Teresa Lee; Jeremy Leipzig; Alexander Lopez; Shrikant M Mane; Laura E Mitchell; Jane W Newburger; Michael Parfenov; Itsik Pe'er; George Porter; Amy E Roberts; Ravi Sachidanandam; Stephan J Sanders; Howard S Seiden; Mathew W State; Sailakshmi Subramanian; Irina R Tikhonova; Wei Wang; Dorothy Warburton; Peter S White; Ismee A Williams; Hongyu Zhao; Jonathan G Seidman; Martina Brueckner; Wendy K Chung; Bruce D Gelb; Elizabeth Goldmuntz; Christine E Seidman; Richard P Lifton
Journal:  Nature       Date:  2013-05-12       Impact factor: 49.962

View more
  24 in total

Review 1.  Advances in understanding the association between Down syndrome and Hirschsprung disease (DS-HSCR).

Authors:  S W Moore
Journal:  Pediatr Surg Int       Date:  2018-09-14       Impact factor: 1.827

Review 2.  Synthetic combinations of missense polymorphic genetic changes underlying Down syndrome susceptibility.

Authors:  Rebecca A Jackson; Mai Linh Nguyen; Angela N Barrett; Yuan Yee Tan; Mahesh A Choolani; Ee Sin Chen
Journal:  Cell Mol Life Sci       Date:  2016-05-31       Impact factor: 9.261

3.  Plasma Amyloid Beta 1-42 and DNA Methylation Pattern Predict Accelerated Aging in Young Subjects with Down Syndrome.

Authors:  Rima Obeid; Ulrich Hübner; Marion Bodis; Juergen Geisel
Journal:  Neuromolecular Med       Date:  2016-05-27       Impact factor: 3.843

Review 4.  Genetic and epigenetic pathways in Down syndrome: Insights to the brain and immune system from humans and mouse models.

Authors:  Y Eugene Yu; Zhuo Xing; Catherine Do; Annie Pao; Eun Joon Lee; Sharon Krinsky-McHale; Wayne Silverman; Nicole Schupf; Benjamin Tycko
Journal:  Prog Brain Res       Date:  2019-10-24       Impact factor: 2.453

5.  DSCR1-mediated TET1 splicing regulates miR-124 expression to control adult hippocampal neurogenesis.

Authors:  Chiyeol Choi; Taehoon Kim; Karen T Chang; Kyung-Tai Min
Journal:  EMBO J       Date:  2019-06-11       Impact factor: 11.598

Review 6.  Mouse-based genetic modeling and analysis of Down syndrome.

Authors:  Zhuo Xing; Yichen Li; Annie Pao; Abigail S Bennett; Benjamin Tycko; William C Mobley; Y Eugene Yu
Journal:  Br Med Bull       Date:  2016-10-27       Impact factor: 4.291

7.  Whole genome bisulfite sequencing of Down syndrome brain reveals regional DNA hypermethylation and novel disorder insights.

Authors:  Benjamin I Laufer; Hyeyeon Hwang; Annie Vogel Ciernia; Charles E Mordaunt; Janine M LaSalle
Journal:  Epigenetics       Date:  2019-05-06       Impact factor: 4.528

8.  Comparative genome-wide DNA methylation analysis in myocardial tissue from donors with and without Down syndrome.

Authors:  Romina B Cejas; Jie Wang; Rachael Hageman-Blair; Song Liu; Javier G Blanco
Journal:  Gene       Date:  2020-08-27       Impact factor: 3.913

Review 9.  Aneuploidy and gene expression: is there dosage compensation?

Authors:  Shihoko Kojima; Daniela Cimini
Journal:  Epigenomics       Date:  2019-11-22       Impact factor: 4.778

Review 10.  Down syndrome.

Authors:  Stylianos E Antonarakis; Brian G Skotko; Michael S Rafii; Andre Strydom; Sarah E Pape; Diana W Bianchi; Stephanie L Sherman; Roger H Reeves
Journal:  Nat Rev Dis Primers       Date:  2020-02-06       Impact factor: 52.329

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.