Defective folate metabolism causes germline epigenetic instability and distinguishesHiraas a phenotype inheritance biomarker

Defective folate metabolism causes germline epigenetic instability and distinguishes Hira as a phenotype inheritance biomarker | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Defective folate metabolism causes germline epigenetic instability and distinguishes Hira as a phenotype inheritance biomarker View ORCID Profile Georgina E.T. Blake , View ORCID Profile Xiaohui Zhao , View ORCID Profile Hong wa Yung , View ORCID Profile Graham J. Burton , View ORCID Profile Anne C. Ferguson-Smith , View ORCID Profile Russell S. Hamilton , View ORCID Profile Erica D. Watson doi: https://doi.org/10.1101/2020.05.21.109256 Georgina E.T. Blake 1 Department of Physiology, Development & Neuroscience, University of Cambridge , Cambridge UK 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Georgina E.T. Blake Xiaohui Zhao 1 Department of Physiology, Development & Neuroscience, University of Cambridge , Cambridge UK 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Xiaohui Zhao Hong wa Yung 1 Department of Physiology, Development & Neuroscience, University of Cambridge , Cambridge UK 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hong wa Yung Graham J. Burton 1 Department of Physiology, Development & Neuroscience, University of Cambridge , Cambridge UK 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Graham J. Burton Anne C. Ferguson-Smith 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK 3 Department of Genetics, University of Cambridge , Cambridge, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Anne C. Ferguson-Smith Russell S. Hamilton 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK 3 Department of Genetics, University of Cambridge , Cambridge, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Russell S. Hamilton Erica D. Watson 1 Department of Physiology, Development & Neuroscience, University of Cambridge , Cambridge UK 2 Centre for Trophoblast Research, University of Cambridge , Cambridge UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Erica D. Watson For correspondence: edw23{at}cam.ac.uk Abstract Full Text Info/History Metrics Data/Code Preview PDF ABSTRACT The mechanism behind transgenerational epigenetic inheritance (TEI) is unclear, particularly through the maternal grandparental line. We previously showed that disruption of folate metabolism in mice by the Mtrr gt hypomorphic mutation results in TEI of congenital malformations. Either maternal grandparent can initiate this phenomenon, which persists for at least four wildtype generations. In this work, we use a genome-wide approach to reveal genetic stability in the Mtrr gt model and epigenome-wide differential DNA methylation in the germline of Mtrr +/gt maternal grandfathers. While epigenetic reprogramming occurs, wildtype grandprogeny and great grandprogeny exhibit transcriptional memory of germline methylation defects. One region encompasses the Hira gene, which is misexpressed in embryos at least until the F3 generation in a manner that distinguishes Hira transcript expression as a biomarker of maternal phenotypic inheritance. INTRODUCTION Environmental stressors can impact an individual’s health and that of their progeny 1 – 5 . Phenotypic risk that persists for several generations in the absence of the stressor is termed transgenerational epigenetic inheritance (TEI) 6 . While the mechanism is unclear, this non-conventional inheritance likely occurs independent of DNA base-sequence mutations and involves the inheritance of an epigenetic factor(s) via the germline 6 , 7 . Candidate factors in mammals include: DNA methylation, histone modifications, and/or non-coding RNA 1 , 2 , 4 , 8 – 10 . How an epigenetic message resists reprogramming and is transmitted between one or even multiple generations to cause disease remains elusive. Few mammalian models of TEI exist and most focus on paternal inheritance 1 , 2 , 8 – 11 . We reported the Mtrr gt mouse line, a rare model of maternal grandparental TEI in which congenital malformations are transgenerationally inherited for at least four wildtype generations 3 ( Supplementary Fig. 1b-c ). Phenotype inheritance persists even after blastocyst transfer of grandprogeny into control uteri ( Supplementary Fig. 1d ) indicating that TEI occurred independent of the maternal environment and instead via the germline 3 . MTRR (methionine synthase reductase) is a key enzyme required for one-carbon metabolism (i.e., folate and methionine metabolism; Supplementary Fig. 1a ) 12 – 14 . Folate is a well-known vitamin important for neural tube closure, yet its function in development is complex and poorly understood. One-carbon metabolism is required for thymidine synthesis 15 and cellular methylation. Indeed, it transmits methyl groups for the methylation of homocysteine by methionine synthase (MTR) to form methionine and tetrahydrofolate 16 . Methionine acts as a precursor for S-adenosylmethionine (SAM), which serves as the sole methyl-donor for substrates involved in epigenetic regulation (e.g., DNA, RNA, histones) 17 – 19 . MTRR activates MTR through the reductive methylation of its vitamin B 12 cofactor 14 ( Supplementary Fig. 1a ). Consequently, progression of one-carbon metabolism requires MTRR to maintain genetic and epigenetic stability. The hypomorphic Mtrr gt mutation reduces wildtype Mtrr transcript expression in mice 3 , 12 and consequently disrupts one-carbon metabolism by diminishing MTR activity 12 . Similar to humans with an MTRR mutation 13 , 20 – 22 or dietary folate deficiency 23 , Mtrr gt/gt mice display hyperhomocysteinemia 3 , 12 and macrocytic anaemia 24 , as well as altered DNA methylation patterns associated with gene misexpression 3 and a range of developmental phenotypes at midgestation (e.g., growth defects and/or congenital malformations including heart, placenta, and neural tube closure defects) 3 . Therefore, Mtrr gt mice are suitable for studying defective folate metabolism. Crucially, the Mtrr gt mouse line is a model of maternal grandparental TEI 3 . Through highly-controlled genetic pedigrees ( Supplementary Fig. 1b-c ), we demonstrated that F0 generation Mtrr +/gt male or female mice can initiate TEI of developmental phenotypes in the wildtype ( Mtrr +/+ ) descendants until the F4 generation 3 . The types of phenotypes at embryonic day (E) 10.5 are similar to those in Mtrr gt/gt conceptuses (see above) 3 . Regardless of whether an F0 Mtrr +/gt male or female initiates TEI, the spectrum and frequency of developmental phenotypes in the F2-F4 wildtype generations are largely comparable between pedigrees. An exception is the F1 generation where phenotypic risk at E10.5 occurs only when individuals are derived from an F0 Mtrr +/gt female ( Supplementary Fig. 1b ) 3 . Despite an absence of gross phenotypes at E10.5, F1 wildtype mice derived from F0 Mtrr +/gt males display indicators of direct epigenetic inheritance including locus-specific epigenetic dysregulation in placentas associated with gene misexpression at E10.5 3 , a hematopoietic phenotype later in life 24 , and the ability to perpetuate TEI in their offspring similar to F1 wildtype females derived from an Mtrr +/gt female 3 . Altogether, TEI originates in gametes from F0 Mtrr +/gt males or females leading to phenotypic inheritance via the F1 wildtype daughters until the F4 wildtype generation 3 . The mechanism is currently unclear. In this work, we investigate potential mechanism(s) of TEI in the Mtrr gt model using a genome-wide approach. First, we demonstrate that Mtrr gt/gt mice are genetically stable and hence reassert focus on an epigenetic mechanism. Second, we show that germline DNA methylation is altered in F0 Mtrr +/gt males. F0 sperm were chosen for analysis because: i) F0 Mtrr +/gt males initiate TEI in a similar manner to F0 Mtrr +/gt females, ii) sperm are more experimental tractable than oocytes, and iii) when assessing heritable effects, the uterine environment does not need to be controlled for in F0 Mtrr +/gt males. Even though differentially methylated regions (DMRs) in sperm of F0 Mtrr +/gt males are reprogrammed in somatic tissue of wildtype F1 and F2 progeny, our data shows evidence of transcriptional memory of germline epigenetic disruption that persists at least until the F3 generation. Transcriptional memory of sperm DMRs includes misexpression of Hira , a gene important for chromatin stability 25 , 26 and ribosome assembly 27 , which we propose as a biomarker and potential mediator of maternal phenotypic inheritance in the Mtrr gt model. RESULTS Genetic stability in Mtrr gt mice Since one-carbon metabolism is directly linked to DNA synthesis 15 , we first addressed whether the Mtrr gt allele influences genetic stability. Whole genome sequencing (WGS) was performed on phenotypically normal C57Bl/6J control embryos (N=2) and Mtrr gt/gt embryos with congenital malformations (N=6) ( Supplementary Fig. 1c,f ). DNA libraries were sequenced separately resulting in ∼30x coverage per embryo (∼3.5 x 10 8 paired-end reads/genome). The sequenced genomes were compared to the C57Bl/6J reference genome to identify structural variants (SVs) and single nucleotide polymorphisms (SNPs). The Mtrr gt mutation was generated by a gene-trap (gt) insertion into intron 9 of the Mtrr gene (Chr13) in the 129P2Ola/Hsd mouse strain before eight generations of backcrossing into the C57Bl/6J strain 3 . As a result, the majority of variants identified in Mtrr gt/gt embryos were located on Chr13 in the genomic region surrounding the Mtrr locus ( Supplementary Fig. 2a-b ). These variants included the gene-trap and several SNPs that showed sequence similarity to the 129P2Ola/Hsd genome and likely persisted due to Mtrr gt genotype selection and regional crossover frequency. Variant identification in this region acted as an internal positive control of our bioinformatic method, demonstrating that it is capable of distinguishing genetic differences between experimental groups. Using these SNPs, we defined a 20 Mb region of 129P2Ola/Hsd sequence surrounding the Mtrr gt allele ( Fig. 1a ). When this region was bioinformatically masked, C57Bl/6J and Mtrr gt/gt embryos contained a similar mean (± sd) frequency of SNPs (C57Bl/6J: 4,871 ± 791 SNPs/embryo; Mtrr gt/gt : 5,138 ± 398 SNPs/embryo; p=0.781) and SVs (C57Bl/6J: 342 SVs/embryo; Mtrr gt/gt : 301 SVs/embryo; p=0.6886; Fig. 1b,c ) implying that the de novo mutation rate was unchanged by the Mtrr gt/gt mutation. These values were in line with expected de novo mutation rates 28 . Only 25 (21 SNPs and 4 SVs) variants were present in all six Mtrr gt/gt embryos and absent in C57Bl/6J embryos ( Supplementary Fig. 2e,f , Supplementary Tables 1 - 2 ). When all SNPs and SVs were considered, the majority represented non-coding variants or were located in non-coding regions ( Supplementary Fig. 2c,d ). Moreover, genetic variation within the masked region had minimal functional effect (beyond the gene-trap insertion) since no variant overlapped with a known enhancer and expression of individual genes was similar among C57Bl/6J, 129P2Ola/Hsd and 4 Mtrr gt/gt mice ( Fig. 1a,d ). Genomic stability was further supported by the preserved repression of transposable elements 29 , 30 in Mtrr gt/gt tissue ( Fig. 1e ) despite global DNA hypomethylation caused by the Mtrr gt/gt mutation 3 . Overall, these data support genetic integrity within the Mtrr gt model, and that phenotypic inheritance was unlikely caused by an increased frequency of de novo mutation. Therefore, focus shifted to an epigenetic mechanism. Download figure Open in new tab Figure 1. The Mtrr gt mouse line is genetically stable. a-c Whole genome sequencing (WGS) of normal C57Bl/6 embryos (N=2 embryos) and severely affected Mtrr gt/gt embryos (N=6 embryos) at E10.5 to determine the frequency of genetic variants compared to the C57Bl/6J reference genome. a The frequency of 129P2Ola/Hsd single nucleotide polymorphisms (SNPs) in the region surrounding the gene-trap insertion site in the Mtrr gene (red line). The majority of genes within the 20 Mb region surrounding the Mtrr gene are shown below the graph. b, c The average number of ( b ) SNPs and ( c ) structural variants (SVs) per embryo in C57Bl/6 embryos (C57, black bars) and Mtrr gt/gt embryos ( gt/gt , white bars). The 20 Mb region shown in ( a ) was masked when calculating the average number of genetic variants in ( b, c ). Data is plotted as mean ± standard deviation (sd). Independent t test. d Graphs showing RT-qPCR analysis of selected genes (highlighted red in a ) in embryos (E10.5), placentas (E10.5) and/or adult testes from C57Bl/6J (black bars), 129P2Ola/Hsd (grey bars) and phenotypically-normal Mtrr gt/gt (blue bars) mice. e Data indicating RNA expression of specific groups of transposable elements as determined by RT-qPCR in C57Bl/6J tissue (black bars) and Mtrr gt/gt tissue (blue bars: phenotypically normal; white bars: severely affected (SA)). Adult liver and placenta at E10.5 were assessed. Data from RT-qPCR analyses in d , e are shown as mean ± sd and relative to C57Bl/6J tissue levels (normalized to 1). N=5-6 embryos, placentas or livers/ experimental group. One-way ANOVA with Dunnett’s multiple comparison test, *p<0.05; **p<0.01. View this table: View inline View popup Download powerpoint Table 1 Sperm DMRs per male genotype in nucleosome retention or reprogramming resistant regions. Germline DNA methylation is altered in the Mtrr gt model MTRR plays a direct role in the transmission of one-carbon methyl groups for DNA methylation 3 , 12 , 14 . Therefore, germline DNA methylation was considered as a potential mediator of phenotype inheritance. Since an Mtrr +/gt female or male can initiate TEI ( Supplementary Fig. 1b ) 3 and due to the experimental tractability of male gametes, we focussed our analysis on sperm. Spermatogenesis and male fertility are normal in Mtrr +/+ , Mtrr +/gt , and Mtrr gt/gt males 31 . Mature spermatozoa were collected from caudal epididymides of C57Bl/6J, Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt mice ( Supplementary Fig. 1c,e,f ) and sperm purity was confirmed by assessing imprinted regions of known methylation status via bisulfite pyrosequencing ( Supplementary Fig. 3a ). Global 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) levels were consistent across all Mtrr genotypes relative to C57Bl/6J controls as determined by mass spectrometry ( Fig. 2a ). Download figure Open in new tab Figure 2. Characterization of differential DNA methylation in spermatozoa from Mtrr gt mouse line. a Global 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) in spermatozoa from C57Bl/6J (black bars), wildtype ( Mtrr +/+ ; purple bars), Mtrr +/gt (green bars) and Mtrr gt/gt (blue bars) adult males (N=9 males/genotype analysed in 3 pools/genotype) as assessed by mass spectrometry. Data is presented as ratio of methylated cytosines per genomic cytosines (mean ± standard deviation (sd)). One-way ANOVA. b-c Methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq) of spermatozoa DNA from Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males relative to C57Bl/6J controls was performed to determine differentially methylated regions (DMRs). N=8 males/group. b An intersectional analysis of DMRs by Mtrr genotype. c A heat map plotting log 2 FoldChange of DNA methylation in spermatozoa from Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males compared to C57Bl/6J males (p<0.05). DMRs that were common between all Mtrr genotypes, paired between two Mtrr genotypes, or unique to a single Mtrr genotype when compared to C57Bl/6J controls are shown. d Examples of sperm DMRs identified via MeDIP-seq and validated by bisulfite pyrosequencing from wildtype ( Mtrr +/+ ) (purple circles), Mtrr +/gt (green circles), or Mtrr gt/gt (blue circles) males compared to C57Bl/6J sperm (black circles) N=8 males/group including four males from the MeDIP-seq analysis and four independent males. Data is shown as percentage methylation at each CpG site assessed (mean ± sd). Schematic of each DMR is is indicated in relation to the closest gene. Two-way ANOVA with Sidak’s multiple comparisons test performed. **p<0.01, ***p<0.0001. See also Fig. 3 and Supplementary Fig. 4 . e-g Relative distribution of methylated regions identified via MeDIP-seq in C57Bl/6J sperm (background methylome) and sperm DMRs from Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males among e unique sequences and repetitive elements, f coding and non-coding regions, and g CpG islands (CGIs), shores and shelves. e and g , Chi-squared test; f , Two-way ANOVA with Dunnett’s multiple comparison test. To analyse genome-wide distribution of sperm DNA methylation, methylated DNA immunoprecipitation followed by sequencing (MeDIP-seq) was performed. This approach allowed the unbiased detection of locus-specific changes in DNA methylation by identifying clusters of differentially methylated cytosines, thus reducing the potential impact of single-nucleotide variants 4 , 32 . MeDIP libraries of sperm DNA were prepared using eight males each from C57Bl/6J, Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt genotypes ( Supplementary Fig. 3b ). Sequencing generated 179 million paired-end mappable reads on average per group (C57Bl/6J: 164 million reads; Mtrr +/+ : 172 million reads; Mtrr +/gt : 203 million reads; Mtrr gt/gt : 179 million reads). Using MEDIPS package 33 , each Mtrr genotype was independently compared to C57Bl/6J controls. Loci of >500 bp with a methylation change of >1.5-fold and p<0.01 were defined as DMRs. The number of sperm DMRs identified increased with the severity of Mtrr genotype: 91 DMRs in Mtrr +/+ males, 203 DMRs in Mtrr +/gt males and 599 DMRs in Mtrr gt/gt males ( Fig. 2b,c ). The presence of DMRs in sperm from Mtrr +/+ males indicated a parental effect of the Mtrr gt allele on offspring germline methylome since Mtrr +/+ males derive from Mtrr +/gt intercrosses ( Supplementary Fig. 1 e ). Hypo- and hypermethylated regions were identified in each Mtrr genotype when compared to C57Bl/6J controls ( Fig. 2c ), consistent with earlier findings in placentas 3 . These data suggested that the Mtrr gt allele was sufficient to dysregulate sperm DNA methylation. To ensure the robustness and reliability of the MeDIP-seq data, we randomly selected hyper- and hypomethylated DMRs to validate using bisulfite pyrosequencing. Sperm DNA from C57Bl/6J, Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males was assessed (N=8 males/group: four sperm samples from MeDIP-seq experiment plus four independent samples). DMRs were validated in the Mtrr genotype in which they were identified ( Figs. 2d , 3 , Supplementary Fig. 4 ). The overall validation rate was 94.1% in hypomethylated DMRs and 58.3% in hypermethylated DMRs ( Supplementary Table 3 ) and indicated a high degree of corroboration between techniques. The majority of DMRs that did not validate showed extensive methylation (>80% CpG methylation) in C57Bl/6J sperm and were identified as hypermethylated in the MeDIP-seq experiment ( Supplementary Fig. 4 ). This might reflect some false positives in line with another study 4 . Download figure Open in new tab Figure 3. Sperm DMRs are reprogrammed in somatic tissue of F1-F2 wildtype generations. CpG methylation at specific sperm differentially methylated regions (DMRs) identified in F0 Mtrr +/gt males was assessed in the F1 and F2 wildtype embryos and placentas at E10.5. Pedigrees indicate specific mating scheme. a-j Schematic drawings of each DMR (green rectangles) assessed indicate its relationship to the closest gene (black) and enhancer (grey line) are followed by graphs showing the average percentage of methylation at individual CpGs for the corresponding DMR as determined by bisulfite pyrosequencing. In each graph, methylation was assessed in sperm from F0 Mtrr +/gt males (green circles), phenotypically normal F1 wildtype ( Mtrr +/+ ) embryos and placentas at E10.5 (orange circles), and phenotypically normal (purple circles) or severely affected (pink circles) F2 wildtype embryos and placentas at E10.5. C57Bl/6J (black circles) are shown as controls. Sperm: N=6-8 males/experimental group; Embryos: N=4-5 embryos/experimental group; Placentas: N=4-8 C57Bl/6J placentas, N=7-8 F1 or F2 wildtype placentas. Data is shown as mean ± sd for each CpG site. Two-way ANOVA, with Sidak’s multiple comparisons test, performed on mean methylation per CpG site per genotype group. *p<0.05, **p<0.01, ***p<0.001. Pedigree legend: circle, female; square, male; blue outline, C57Bl/6J control; black outline, Mtrr gt mouse line; white filled, Mtrr +/+ ; half-white/halfblack filled, Mtrr +/gt . For most DMRs assessed, methylation change was consistent across all CpG sites and the absolute change in CpG methylation ranged from 10 to 80% of control levels ( Figs. 2d , 3 , Supplementary Fig. 4 ). Within each genotypic group, a high degree of inter-individual consistency of methylation change was also observed. Therefore, we conclude that the Mtrr gt mutation, or parental exposure to it as in Mtrr +/+ males, is sufficient to lead to distinct DNA methylation changes in sperm. Most DMRs associate with metabolic dysregulation not genetic effects A proportion of the DMRs were located within the region around the gene-trap insertion site in Mtrr +/gt and Mtrr gt/gt males ( Fig. 1a , Supplementary Fig. 5b,c ), consistent with Mtrr gt/gt liver 34 and suggesting that the gene-trap or underlying 129P2Ola/Hsd sequence might epigenetically dysregulate the surrounding region. However, comparison of the MeDIP-seq and WGS data sets revealed that genetic variation did not influence DMR calling to a great extent since only a small proportion (2.8-5.5%) of these DMRs contained one or more SNP. Eight DMRs overlapped with known enhancers ( Supplementary Table 4 ), none of which associated with promoters 35 containing a genetic variant. Outside of the Mtrr genomic region, 54 DMRs were common to Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males ( Fig. 2b,c , Supplementary Table 5 ) and were primarily located in distinct chromosomal clusters ( Supplementary Fig. 5a-d ). These data implicate epigenetic hotspots or underlying genetic effects. However, beyond a polymorphic duplication on Chr19 in the C57Bl/6J strain 36 that accounted for a minor number of DMRs (2.5-15.8% of DMRs), no DMRs overlapped with an SV or were located <1 kb of an SV. Once potential genetic effects were accounted for, the majority of sperm DMRs in Mtrr +/+ and Mtrr +/gt males (76/91 DMRs and 142/203 DMRs, respectively), and a proportion of sperm DMRs in Mtrr gt/gt males (174/599 DMRs) were attributed to the long-term metabolic consequences of the Mtrr gt mutation. Sperm DMR genomic distribution and potential regulatory function DMR distribution was determined to explore regional susceptibility of the sperm methylome to the effects of the Mtrr gt allele. First, the sperm ‘background methylome’ was established to resolve the expected genome-wide distribution of CpG methylation (see Methods). By comparing the regional distribution of sperm DMRs to the background methylome, we revealed that DMRs in all Mtrr genotypes were not significantly enriched in repetitive regions ( Fig. 2e ). However, sperm DMRs in Mtrr +/+ and Mtrr +/gt males were over-represented in introns and exons, and under-represented in intergenic regions (p<0.0003, Chi-squared test; Fig. 2f ). This was not the case for Mtrr gt/gt males since DMRs were proportionately distributed among most genomic regions ( Fig. 2f ). While the majority of sperm DMRs were located within CpG deserts, a proportion of DMRs from Mtrr +/gt and Mtrr gt/gt males were enriched in CpG islands (p<0.0014, Chi-squared; Fig. 2g ), which has implications for gene regulatory control. Lastly, when considering only the subset of common DMRs shared by all Mtrr genotypes, a similar genomic distribution to Mtrr +/+ and Mtrr +/gt males was observed ( Supplementary Fig. 5d,e ). During sperm maturation, histones are replaced by protamines 37 . However, ∼1% of histone-containing nucleosomes are retained 38 providing scope for epigenetic inheritance 39 . Nucleosome retention occurs primarily at promoters of developmentally-regulated genes and gene-poor repeat regions, though regional distribution and frequency differs between reports 40 , 41 . To determine whether sperm DMRs in Mtrr males were enriched in known sites of nucleosome retention, we utilized the MNase-seq dataset from C57Bl/6J spermatozoa in Erkek et al . 41 . First, by randomly selecting 10,000 regions of 500 bp as a proxy for DMRs, we determined that the expected frequency of DMR overlap with sites of nucleosome retention was 1.94%. Crucially, we observed that 14.5-34.1% of DMRs identified in sperm from Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males were located in nucleosome retention regions ( Table 1 ), indicating a significant enrichment (p<0.0001, binomial test). Therefore, these DMRs represented candidate regions for epigenetic inheritance. To better understand the normal epigenetic signatures within regions identified as sperm DMRs and to predict a potential gene regulatory role, mean enrichment for histone modifications and/or chromatin accessibility in mouse spermatozoa 42 , epiblast and extraembryonic ectoderm at E6.5 43 was determined using published ChIP-seq and ATAC-seq data sets. All DMRs, except those surrounding the Mtrr gene-trapped site, were analysed (N=379 DMRs from all Mtrr genotypes combined) alongside 379 randomly selected regions representing the ‘baseline genome’ (see Methods). Compared to the sperm baseline genome, the majority of our DMRs were likely to associate with a closed chromatin state due to collective enrichment for protamine 1 (PRM1) and repressive histone mark H3K9me3, but not active histone marks (e.g., H3K4me1, H3K27ac) or Tn5 transposase sensitive sites (THSS) 42 ( Supplementary Fig. 6a,b ). This finding reinforces heterogeneity of DMR association with retained nucleosomes 41 or protamines ( Table 1 ). In contrast, the DMRs were more likely in an open chromatin conformation state in epiblast and extraembryonic ectoderm at E6.5 based on collective enrichment for THSS when compared to tissue-specific baseline genomes 43 ( Supplementary Fig. 6c ). Therefore, it is possible that the genomic regions identified as DMRs in Mtrr sperm have a regulatory role during development. Some DMRs were located in regions of reprogramming resistance DNA methylation is largely reprogrammed during pre-implantation development and in the developing germline 44 , 45 to ‘reset’ the methylome between each generation. Recently, several loci were identified as ‘reprogramming resistant’ 46 – 48 and thus, are implicated in epigenetic inheritance. Using published methylome data sets 46 , 47 , we determined that 40.7-54.3% of sperm DMRs across all Mtrr genotypes fell within loci resistant to pre-implantation reprogramming ( Table 1 ). Sixteen of these DMRs were common among Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males. Fewer DMRs correlated with regions resistant to germline reprogramming (2.2-3.8% of DMRs/ Mtrr genotype; Table 1 ) or both pre-implantation and germline reprogramming (2.0-2.7% of DMRs/ Mtrr genotype; Table 1 ). Only one DMR located in a region resistant to germline reprogramming was common to all Mtrr genotypes. Interestingly, several DMRs were characterized as regions of reprogramming resistance 46 , 47 and nucleosome retention 41 ( Table 1 ). Overall, differential methylation of these key regions in sperm of Mtrr gt males might have important implications for epigenetic inheritance. Sperm DMRs are reprogrammed in wildtype F1 and F2 generations TEI in the Mtrr gt model occurs via the maternal grandparental lineage 3 ( Supplementary Fig. 1b ). To determine the heritability of germline DMRs, bisulfite pyrosequencing was used to validate ten sperm DMRs from F0 Mtrr +/gt males in tissue of wildtype F1 and F2 progeny. The advantage of assessing inheritance of DNA methylation in F0 sperm rather than in F0 oocytes was that potential confounding effects of the F0 uterine environment could be avoided. Candidate DMRs were hyper- or hypomethylated, and localized to regions of reprogramming resistance and/or to intra- or intergenic regions ( Supplementary Table 6 ). In general, all DMRs tested lost their differential methylation in wildtype F1 and F2 embryos and placentas at E10.5, and showed DNA methylation patterns similar to C57Bl/6J tissue ( Fig. 3 ). This result occurred even when wildtype F2 conceptuses displayed congenital malformations ( Fig. 3 ). DMRs were also assessed in Mtrr gt/gt conceptuses at E10.5 to determine whether these regions were capable of differential methylation outside of the germline. In a manner similar to sperm from Mtrr +/gt males ( Fig. 3 ), seven out of 10 DMRs were hypermethylated in Mtrr gt/gt embryos and/or placentas compared to control conceptuses ( Supplementary Fig. 7a-j ). In this case, it was unclear whether DNA methylation in these regions resisted epigenetic reprogramming or was erased and abnormally re-established/ maintained due to intrinsic Mtrr gt/gt homozygosity. Overall, altered patterns of DNA methylation in sperm of Mtrr +/gt males were not evident in somatic tissue of wildtype progeny and grandprogeny. This result was reminiscent of mouse models of parental exposure to environmental stressors (e.g., maternal under-nutrition 4 , paternal folate deficiency 49 , or paternal cigarette smoking 50 ), which induced sperm DMRs associated with phenotypes in the direct offspring even though the DMRs were resolved in offspring somatic tissue. As a result, other epigenetic mechanisms (e.g., germline RNA content and/or histone modifications) with 5mC are implicated in phenotypic inheritance. Transcriptional memory of sperm DMRs A previous study in mice suggests that sperm DMRs can associate with perturbed transcription in offspring even when DNA methylation is re-established to normal levels 4 . To assess whether transcriptional memory occurred in the Mtrr +/gt maternal grandfather pedigree, expression of six genes located in or near sperm DMRs from F0 Mtrr +/gt males ( Supplementary Table 6 ) was assessed in F1 and F2 wildtype individuals. While these genes displayed normal expression in F1 tissues ( Fig. 4a-c ), Hira (histone chaperone) , Cwc27 (spliceosome-associated protein), and Tshz3 (transcription factor) were misexpressed in F2 wildtype embryos or adult livers compared to C57Bl/6J controls ( Fig. 4d-f ). This result might reflect transcriptional memory of the associated sperm DMR or wider epigenetic dysregulation in sperm of the F0 Mtrr +/gt males. Download figure Open in new tab Figure 4. Transcriptional memory of some DMR-associated genes in F1 and F2 wildtype somatic tissue. a-f RT-qPCR analysis of mRNA expression of genes located in close proximity to sperm DMRs in a, d embryos at E10.5, b, e placental trophoblast at E10.5, and c, f adult livers of wildtype ( Mtrr +/+ ) F1 and F2 progeny. Tissue from phenotypically normal F1 wildtype individuals (orange bars), and phenotypically normal (purple bars) or severely affected (pink bars) F2 wildtype individuals derived from an F0 Mtrr +/gt male was assessed. C57Bl/6J control tissues (black bars) were assessed as controls. Pedigrees indicate specific mating scheme assessed. Data is plotted as mean ± standard deviation, and is presented as relative expression to C57Bl/6J levels (normalized to 1). N=4-7 individuals per group. Independent t tests or one-way ANOVA with Dunnett’s multiple comparisons tests were performed. **p<0.01, ***p<0.001. Each gene was associated with the following sperm DMR shown in Fig. 3 : Tshz3 , DMR E115; Dynlt1a , DMR E52; Exoc4, DMR E112; March5 , DMR C7; Cwc27 , DMR D20; Hira , DMR A10. Pedigree legend: circle, female; square, male; blue outline, C57Bl/6J control; black outline, Mtrr gt mouse line; white filled, Mtrr +/+ ; halfwhite/ half-black filled, Mtrr +/gt . To further predict whether the Hira , Cwc27 , and Tshz3 DMRs demarcate gene regulatory regions, their specific genetic and epigenetic characteristics beyond CpG methylation were considered. Genomically, the DMRs were located intragenically ( Cwc27 and Tshz3 DMRs) or within 6 kb downstream of the gene ( Hira DMR; Fig. 5a , Supplementary Figs. 8-9). Furthermore, Cwc27 DMR overlapped with a known enhancer ( Supplementary Fig. 8 ) while Hira and Tshz3 DMRs overlapped with CpG islands 51 ( Fig. 5a , Supplementary Fig. 9 ). Next, we assessed the three DMRs for enrichment of specific histone modifications during normal development using published ChIP-seq data sets 35 in wildtype embryonic stem cells (ESCs) and trophoblast stem cells (TSCs). While histone marks were largely absent at all three DMRs in TSCs, enrichment for one or more repressive histone mark (e.g., H3K4me3 and/or H3K9me3) at these DMRs was apparent in ESCs ( Fig. 5a , Supplementary Fig. 8 - 9 ). Altogether, DMRs identified in sperm of Mtrr +/gt males highlight regions that might be important for transcriptional regulation in the early conceptus by other epigenetic mechanisms. Therefore, future analyses of broader epigenetic marks at these sites are required in the Mtrr gt mouse line. Download figure Open in new tab Figure 5. Epigenetic characteristics of Hira DMR in mice. a Enrichment of DNA binding proteins (CTCF) and histone modifications (H3K27ac, H3K27me3, H3K4me1, H3K4me3, H3K9me3) in the Hira locus on mouse chromosome (Chr) 16 using published data sets 35 of chromatin immunoprecipitation followed by sequencing (ChIP-seq) analyses in cultured wildtype embryonic stem cells (ESCs) and trophoblast stem cells (TSCs). Grey rectangles indicate enrichment peak calling for each histone modification. Red rectangle and grey shading indicated the Hira differentially methylated region (DMR) identified in sperm of Mtrr +/gt and Mtrr gt/gt males. Blue rectangles indicate CpG islands. Green rectangles indicate enhancers. Schematics of protein encoding (brown) and long non-coding RNA (lncRNA) encoding (purple) Hira isoforms are shown. Region of RT-qPCR primer sets 1 and 2 are also indicated. b Partial schematic drawing of Hira transcripts and Hira DMR (red rectangle) in relation to MeDIP-seq reads in sperm from C57Bl/6J (black), wildtype ( Mtrr +/+ ; purple), Mtrr +/gt (green) and Mtrr gt/gt (blue) males. N=8 males per group. c The average percentage methylation at individual CpG sites (mean ± standard deviation) in the Hira DMR in sperm from C57Bl/6J (black circles; N=4 males), Mtrr +/+ (purple circles; N=4 males), Mtrr +/gt (green circles; N=8 males) and Mtrr gt/gt (blue circles; N=8 males) males. Two-way ANOVA with Sidak’s multiple comparisons test performed on mean methylation per CpG site. ***p<0.001. HIRA as a potential biomarker of maternal phenotypic inheritance The importance of the Hira DMR in phenotypic inheritance was further considered based on its known resistance to germline reprogramming 46 , and its potential function in gene regulation ( Fig. 5a ) and transcriptional memory ( Fig. 4d ). HIRA is a histone H3.3 chaperone, which lends itself well to a role in epigenetic inheritance given its broad functionality in transcriptional regulation 26 , maintenance of chromatin structure in the developing oocyte 25 and the male pronucleus after fertilization 27 , and in rRNA transcription and ribosome function 27 . Hira -/- mice 52 and the Mtrr gt mouse line 3 display similar phenotypes including growth defects, congenital malformations, and embryonic lethality by E10.5. Furthermore, Mtrr gt genotypic severity correlated with the degree of hypermethylation in the Hira DMR in sperm ( Fig. 5b,c ) suggesting that the Hira DMR is responsive to alterations in folate metabolism. The potential regulatory legacy of the Hira DMR in sperm was further explored in the Mtrr +/gt maternal grandfather pedigree. The Hira DMR, which was 6 kb downstream of the Hira gene and overlaps with a CpG island and CTCF binding site in ESCs and TSCs ( Fig. 5a ), was substantially hypermethylated in sperm of F0 Mtrr +/gt males compared to controls (39.0 ± 4.1% more methylated CpGs per CpG site assessed; Fig. 5b,c ). As with the other sperm DMRs assessed ( Fig. 3 ), the Hira DMR was reprogrammed in F1-F3 wildtype embryos and placentas at E10.5 ( Fig. 3a , Supplementary Fig. 10a ). While we originally assessed Hira mRNA in the F1-F2 generations in the maternal grandfather pedigree ( Fig. 4 ), further analysis revealed that Hira isoforms (mRNA and long non-coding RNA (lncRNA 209); Fig. 5a ) were differentially regulated at E10.5 ( Fig. 6a-c ). Hira lncRNA function is unknown, though lncRNA-based mechanisms often control cell fates during development by influencing nuclear organization and transcriptional regulation 53 . Notably, this pattern of RNA expression was associated with generational patterns of phenotypic inheritance. For instance, we observed down-regulation of Hira mRNA in F2-F3 wildtype embryos and not F1 wildtype embryos at E10.5 ( Fig. 6a-c ). Conversely, significant up-regulation of Hira lncRNA expression was apparent only in F1 wildtype embryos at E10.5 ( Fig. 6a-c ). This expression pattern was embryo-specific since the corresponding placentas showed normal Hira transcript levels in each generation assessed compared to controls ( Fig. 6a-b ). Since phenotypes at E10.5 were apparent in F2 generation onwards, yet were absent in the F1 generation of the Mtrr +/gt maternal grandfather pedigree 3 , embryo-specific Hira RNA misexpression reflected the pattern of phenotypic inheritance. Download figure Open in new tab Figure 6. Dysregulation of Hira RNA in F1-F3 wildtype conceptuses at E10.5 aligns with a pattern of maternal phenotypic inheritance. a-d RT-qPCR data showing Hira mRNA (solid bars, primer set 1) and Hira lncRNA (striped bars, primer set 2) in embryos and placentas at E10.5. The following conceptuses were assessed from the indicated pedigree: a F1 wildtype ( Mtrr +/+ ) conceptuses derived from F0 Mtrr +/gt males (orange bars; N=4-8 normal embryos and placentas), b F2 wildtype conceptuses derived from F0 Mtrr +/gt males (purple and pink bars; N=5-8 embryos and placentas/phenotype), c F3 wildtype conceptuses derived from F0 Mtrr +/gt males (teal and turquoise bars; N=3-4 embryos/phenotype) and d F1 wildtype (orange bars, N=3-7 embryos/phenotype), F2 wildtype (pink and purple bars; N=5-7 embryos/phenotype, and F3 wildtype conceptuses (teal and turquoise bars; N=3-5 embryos/phenotype) derived from F0 Mtrr +/gt females. C57Bl/6J conceptuses (black bars; N=4-8 embryos and placenta/experiment) were controls. Phenotypically-normal (n) and severely affected (a) conceptuses were assessed. e, f Western blot analysis showing HIRA protein expression in embryos (N=4-9) and placentas (N=3-8) of F1 wildtype (orange bars) and F2 wildtype (purple bars) conceptuses derived from either e F0 Mtrr +/gt males or f F0 Mtrr +/gt females. C57Bl/6J embryos and placentas (black bars) were assessed as controls. Western blots showing HIRA protein with β-actin as a loading control are shown, and quantified using the background subtraction method. HIRA protein levels were first normalised to β-actin. All data was plotted as mean ± standard deviation and relative to C57Bl/6J (normalised to 1). Independent t tests or Kruskal-Wallis test with Dunn’s multiple comparison test. *p<0.05, **p<0.01, ***p<0.001. Pedigree legend, circle, female; square, male; blue outline, C57Bl/6J line; black outline, Mtrr gt mouse line; white fill, Mtrr +/+ ; half black-half white fill, Mtrr +/gt ; black fill, Mtrr gt/gt . To further investigate a potential link between Hira expression and phenotypic inheritance, we analysed wildtype F1-F3 conceptuses at E10.5 derived from F0 Mtrr +/gt females ( Supplementary Fig. 1b ), of which all generations, including the F1 generation, display a broad spectrum of developmental phenotypes 3 . Supporting our hypothesis, Hira mRNA expression was down-regulated in F1-F3 wildtype embryos derived from an F0 Mtrr +/gt female compared to C57Bl/6J controls ( Fig. 6d ), thus correlating with maternal phenotypic inheritance. As expected, Hira lncRNA transcripts were unchanged in F1 and F3 wildtype embryos ( Fig. 6d ). However, Hira lncRNA was down-regulated in F2 wildtype embryos ( Fig. 6d ), which display the highest frequency of phenotypes among the three generations 3 . Regardless, these data suggested that altered Hira mRNA transcripts are a potential biomarker of maternal phenotypic inheritance. This was because dysregulation of Hira mRNA occurred only in wildtype embryos with high phenotypic risk due to their derivation from an oocyte with Mtrr gt ancestry rather than sperm ( Fig. 7 ). Download figure Open in new tab Figure 7. Proposed model of maternal phenotypic inheritance in Mtrr gt model. A model suggesting how epigenetic instability generated by the Mtrr gt mutation might be differently inherited over multiple generations depending upon whether TEI is initiated by a an oocyte or b sperm of an Mtrr +/gt individual. Trends of Hira mRNA expression are shown for each breeding scheme. Pedigree legend: circle, female; square, male; blue outline, C57Bl/6J control; black outline, Mtrr gt mouse line; white filled, Mtrr +/+ ; half-white/half-black filled, Mtrr +/gt . How the Hira gene is regulated is unknown. Mtrr gt/gt embryos at E10.5, which demonstrate a greater phenotypic risk than the Mtrr +/gt maternal grandparental pedigrees, also displayed dyregulation of Hira mRNA and lncRNA expression ( Supplementary Figs. 7k-m , 10d ). This finding was in association with normal DNA methylation at the Hira DMR in Mtrr gt/gt embryos at E10.5 ( Supplementary Fig. 7b ), implicating additional mechanisms of epigenetic regulation. Histone methylation profiles at the Hira locus in normal ESCs and TSCs indicate a potential role for the Hira promoter and Hira DMR ( Fig. 5a ) in gene regulation that will require future investigation. HIRA protein levels were also dysregulated in Mtrr gt/gt embryos and F2 wildtype embryos and placentas ( Fig. 6e,f , Supplementary Fig. 10e,f ) and not always in a manner predicted by the direction of Hira mRNA expression. For example, there was an increase in HIRA protein levels in F2 wildtype embryos when Hira mRNA was down-regulated ( Fig. 6b,d-f ). This discrepancy might result from defective HIRA protein degradation, a drastic translational up-regulation of HIRA protein to compensate for low mRNA levels, or alternatively, negative feedback to down-regulate Hira mRNA due to high levels of HIRA protein in the embryo. Further work will be required to delineate whether the HIRA chaperone mediates maternal phenotypic inheritance in the Mtrr gt model and other models of TEI. DISCUSSION We investigated potential mechanisms contributing to epigenetic inheritance in Mtrr gt mice, a unique model of mammalian TEI 3 . In the Mtrr gt model, inheritance of developmental phenotypes and epigenetic instability occurs via the maternal grandparental lineage with an F0 Mtrr +/gt male or female initiating the TEI effect 3 . Here, we assessed DNA methylation in spermatozoa to understand how the germline epigenome was affected by the Mtrr gt allele. We chose sperm due to its experimental tractability and to avoid the confounding factors of the F0 uterine environment when assessing epigenetic inheritance via the germline. We identified several distinct DMRs in regions of predicted importance in transcriptional regulation and epigenetic inheritance including regions of nucleosome retention and reprogramming resistance. This result illustrates widespread epigenetic instability in the male germline of the Mtrr gt model, particularly in the F0 Mtrr +/gt males of the maternal grandfather pedigree. While largely resolved in somatic tissue of subsequent wildtype generations, some germline DMRs were associated with transcriptional changes at associated loci in the F1-F3 progeny. This transcriptional memory of a germline DMR persisted for at least three generations, longer than previously reported in another model 4 . This observation indicates additional epigenetic factors beyond DNA methylation in the mechanism of TEI. Furthermore, the histone chaperone gene Hira emerged as a transcriptional biomarker and potential mediator of maternal phenotypic inheritance. The extent to which genetic and epigenetic factors interact in this and other TEI models is unclear. One-carbon metabolism is involved in thymidine synthesis 54 , and DNA breaks triggered by folate deficiency-induced uracil misincorporation was demonstrated in erythrocytes of splenectomised patients 55 and prostate adenoma cells 56 . However, WGS of Mtrr gt/gt embryos excluded genetic instability in the Mtrr gt mouse line because de novo mutations occurred at an expected 28 and comparable frequency to control embryos. The WGS data also discounted alternative phenotype-causing mutations and, when compared to our sperm methylome data set, showed that differential CpG methylation was unlikely due to underlying genetic variation in the Mtrr gt mouse line. Therefore, the epigenetic consequences of the Mtrr gt allele rather than genetic instability are more likely to instigate TEI in this model. Generating alternative Mtrr mutations and/or backcrossing the Mtrr gt allele into a different mouse strain will further assess whether genetics plays a role in TEI. Our data show that inheritance of sperm DMRs by offspring somatic tissue was unlikely, as have other studies 4 , 49 , 50 . Instead, somatic cell lineages might inherit germline epigenetic instability in a broader sense. For instance, despite normal DNA methylation in F1-F3 wildtype embryos and placentas (E10.5) at the genomic locations highlighted by sperm DMRs, epigenetic instability associated with gene misexpression is still evident in F1 and F2 wildtype placentas at several loci 3 . It is possible that abnormalities in the sperm epigenome of F0 Mtrr +/gt males might be reprogrammed and then stochastically and abnormally re-established/maintained in other genomic regions in wildtype offspring. This hypothesis might explain inter-individual phenotypic variability in the F2-F3 generations. However, we showed that sperm of Mtrr +/+ males exhibited several DMRs that overlapped with sperm DMRs in Mtrr +/gt males (representing their fathers). Therefore, reconstruction of specific atypical F0 germline methylation patterns in the F1 wildtype germline is possible in the Mtrr gt model. Vinclozolin toxicant exposure model of TEI shows dissimilar DMRs in spermatozoa of F1 and F3 offspring 8 , which suggests that epigenetic patterns might shift as generational distance from the F0 individual increases. Dietary folate deficiency causes differential methylation in sperm and craniofacial defects in the immediate offspring 49 , though whether it leads to TEI is unknown. There was no overlap of DMRs when sperm methylomes were compared between the diet model and Mtrr +/gt males. This result disputes the existence of folate-sensitive epigenomic hotspots in sperm. However, severity of insult or technical differences (e.g., MeDIP-array 49 versus MeDIP-seq) might explain the discrepancy. Why only one Mtrr gt allele sufficiently initiates TEI is unknown since a direct paramutation effect was not evident 3 and Mtrr +/gt mice do not display similar metabolic derangement to Mtrr gt/gt mice 3 , 12 . Whether specific DNA methylation patterns observed in F0 sperm of the maternal grandfather pedigree are reconstructed 57 , 58 in F1 oocytes is yet-to-be determined. Extensive differences between sperm and oocytes methylomes 59 will make this difficult to resolve and yet also emphasizes that additional epigenetic mechanisms are likely involved, such as histone modifications 10 , sncRNA expression 1 , 9 and/or changes in nucleosome composition and spacing that alter nuclear architecture 59 . Several of these mechanisms implicate regulators like HIRA 25 – 27 (see below). Future studies will explore the extent to which differential epigenetic marks in oocytes from F0 Mtrr +/gt females are reconstructed in oocytes of subsequent generations, though embryo transfer experiments will be required to exclude the confounding effects of the F0 uterine environment 60 . Several recent studies have assessed sncRNA expression (e.g., microRNA or tRNA fragments [tsRNA]) 1 , 2 , 9 in sperm as a mechanism in direct epigenetic inheritance of disease. For example, manipulating paternal diet in mice is sufficient to alter tsRNA content in spermatozoa leading to altered expression of genes associated with MERVL elements in early F1 embryos 9 and metabolic disease in F1 adult offspring 1 . It is possible that sncRNAs in sperm from F0 Mtrr +/gt males are misexpressed and/or abnormally modified 61 , and that this might contribute to TEI mechanisms. While it is currently unclear how sperm ncRNA content causes phenotypic inheritance beyond the F1 generation, genes involved in development of the primordial germ cell population within the F1 wildtype female embryo might be among those affected. Exploring sncRNA content in germ cells of the Mtrr gt model will help to better understand this question. Several sperm DMRs in Mtrr +/gt males (e.g., Cwc27 , Tshz3 , Hira ) demonstrated transcriptional memory in F2-F3 wildtype embryos and adult liver. We focused our analysis on the Hira DMR due to its responsiveness to the severity of the Mtrr gt genotype, the fact that Hira -/- embryos 52 phenocopy embryos in the Mtrr gt model 3 , and because the potential consequences of HIRA dysfunction are multifaceted and implicated in epigenetic inheritance. The HIRA histone chaperone complex regulates histone deposition/recycling required to maintain chromatin integrity in the oocyte and zygote 25 , 26 , 62 . Additionally, HIRA is implicated in rRNA transcription and ribosome assembly in the mouse zygote 27 . Therefore, dysregulation of HIRA expression and/or function in the Mtrr gt model might alter nucleosome spacing and ribosome heterogeneity 63 , 64 with substantial implications for regulation of transcriptional pathways during germ cell and embryo development. Since the F1 progeny differ phenotypically when derived from an F0 Mtrr +/ gt male versus F0 Mtrr +/ gt female 3 , the mechanism initiating TEI potentially differs between sperm and oocytes. The extent of mechanistic overlap is not well understood. Certainly, paternally-inherited epigenetic factors 1 , 2 , 4 , 9 , 10 , 49 , 61 , 65 are better studied than maternally-inherited factors 60 , 66 . The difference in phenotypic severity in the Mtrr gt model might relate to a cytoplasmically-inherited factor in the F1 wildtype zygote ( Fig. 7 ). HIRA is a suitable candidate since maternal HIRA 25 , 67 is involved in protamine replacement by histones in the paternal pronucleus 27 thus perpetuating epigenetic instability. Therefore, in the case of the Mtrr gt model, dysregulation of Hira and/or other maternal factors in oocytes might have a greater impact on epigenetic integrity in the early embryo than when dysregulated in sperm. Overall, we show the long-term transcriptional and phenotypic impact of abnormal folate metabolism on germline DNA methylation and emphasize the complexity of epigenetic mechanisms involved in TEI. Ultimately, our data indicate the importance of normal folate metabolism in both women and men of reproductive age for healthy pregnancies in their daughters and granddaughters. METHODS Ethics statement This research was regulated under the Animals (Scientific Procedures) Act 1986 Amendment Regulations 2012 following ethical review by the University of Cambridge Animal Welfare and Ethical Review Body. Animal model Mtrr Gt (XG334) Byg (MGI:3526159), referred to as Mtrr gt mice, were generated as previously described 3 . Briefly, a β-geo gene-trap (gt) vector was inserted into intron 9 of the Mtrr gene in 129P2Ola/Hsd embryonic stem cells (ESCs). Mtrr gt ESCs were injected into C57Bl/6J blastocysts. Upon germline transmission, the Mtrr gt allele was backcrossed into the C57Bl/6J genetic background for at least eight generations 3 . Mtrr +/+ and Mtrr +/gt mice were produced from Mtrr +/gt intercrosses ( Supplementary Fig. 1e ). Mtrr gt/gt mice were produced from Mtrr gt/gt intercrosses ( Supplementary Fig. 1f ). C57Bl/6J mice from The Jackson Laboratories ( www.jaxmice.jax.org ) and 129P2Ola/Hsd from Envigo (previously Harlan Laboratories [ www.envigo.com ]) were used as controls and were bred in house and separately from the Mtrr gt mouse line ( Supplementary Fig. 1c ). All mice were fed a normal chow diet (Rodent No. 3 breeding chow, Special Diet Services) ad libitum from weaning. A detailed breakdown of the diet was reported previously 3 . Mice were euthanized via cervical dislocation. Genotyping for the Mtrr gt allele and/or sex was performed using PCR on DNA extracted from ear tissue or yolk sac as previously described 3 , 68 , 69 . To determine the multigenerational effects of the Mtrr gt allele in the maternal grandfather, the following mouse pedigree was established ( Supplementary Fig. 1b ). For the F1 generation, F0 Mtrr +/gt males were mated with C57Bl/6J females and the resulting Mtrr +/+ progeny were analysed. For the F2 generation, F1 Mtrr +/+ females were mated with C57Bl/6J males and the resulting Mtrr +/+ progeny were analysed. For the F3 generation, F2 Mtrr +/+ females were mated with C57Bl/6J males and the resulting Mtrr +/+ progeny was analysed. A similar pedigree was established to assess the effects of the Mtrr gt allele in the maternal grandmother with the exception of the F0 generation, which involved the mating of an Mtrr +/gt female with a C57Bl/6J male. Tissue dissection and phenotyping For embryo and placenta collection, timed matings were established and noon on the day that the vaginal plug was detected was considered embryonic day (E) 0.5. Embryos and placentas were dissected at E10.5 in cold 1x phosphate buffered saline and were scored for phenotypes (see below), photographed, weighed, and snap frozen in liquid nitrogen for storage at −80°C. All conceptuses were dissected using a Zeiss SteREO Discovery V8 microscope with an AxioCam MRc5 camera (Carl Zeiss). Livers were collected from pregnant female mice (gestational day 10.5), weighed and snap frozen in liquid nitrogen for storage at −80°C. Both male and female conceptuses at E10.5 were assessed, as no sexual dimorphism is apparent at this stage 70 . While many individual mice were assessed over the course of this study, some of the individual tissue samples were assessed for the expression of multiple genes or for methylation at multiple DMRs. A rigorous phenotyping regime was performed at E10.5 as previously described 3 . Briefly, all conceptuses were scored for one or more congenital malformation including failure of the neural tube to close in the cranial or spinal cord region, malformed branchial arches, pericardial edema, reversed heart looping, enlarged heart, and/or off-centered chorioallantoic attachment. Twinning or haemorrhaging was also scored as a severe abnormality. Conceptuses with severe abnormalities were categorized separately from resorptions, the latter of which consisted of maternal decidua surrounding an indistinguishable mass of fetally-derived tissue. Resorptions were not assessed in this study. Embryos with <30 somite pairs were considered developmentally delayed. Embryos with 30-39 somite pairs but a crown-rump length more than two standard deviations (sd) from the mean crown-rump length of C57Bl/6J control embryos were considered growth restricted or growth enhanced. Conceptuses were considered phenotypically-normal if they were absent of congenital malformations, had 30-39 somite pairs and had crown-rump lengths within two sd of controls. AxioVision 4.7.2 imaging software was used to measure crown-rump lengths (Carl Zeiss). Conceptus size at E10.5 was unaffected by litter size in all Mtrr gt pedigrees assessed 70 . Spermatozoa collection Spermatozoa from cauda epididymides and vas deferens were collected from 16-20 week-old fertile mice using a swim-up procedure as previously described 38 with the following amendments. Spermatozoa were released for 20 minutes at 37 ° C in Donners Medium (25 mM NaHCO3, 20 mg/ml bovine serum albumin (BSA), 1 mM sodium pyruvate and 0.53% (vol/vol) sodium dl-lactate in Donners stock (135 mM NaCl, 5 mM KCl, 1 mM MgSO4, 2 mM CaCl 2 and 30 mM HEPES)). Samples were centrifuged at 500 x g (21°C) for 10 minutes. The supernatant was transferred and centrifuged at 1,300 x g (4°C) for 15 minutes. After the majority of supernatant was discarded, the samples were centrifuged at 1,300 x g (4°C) for 5 minutes. Further supernatant was discarded and the remaining spermatozoa were centrifuged at 12,000 x g for 1 minute and stored at −80°C. Nucleic Acid Extraction For embryo, trophoblast and liver tissue, genomic DNA (gDNA) was extracted using DNeasy Blood and Tissue kit (Qiagen) according to the manufacturer’s instructions. RNA was extracted from tissues using the AllPrep DNA/RNA Mini Kit (Qiagen). For sperm, Solution A (75 mM NaCl pH 8; 25 mM EDTA) and Solution B (10 mM Tris-HCl pH 8; 10 mM EDTA; 1% SDS; 80 mM DTT) were added to the samples followed by RNAse A incubation (37°C, 1 hour) and Proteinase K incubation (55°C, overnight) as was previously described 4 . DNA was extracted using phenol/chloroform/isoamyl alcohol mix (25:24:1) (Sigma-Aldrich) as per the manufacturer’s instructions. DNA was precipitated using 10 M ammonium acetate, 0.1 mg/ml glycogen, and 100% ethanol and incubated at −80°C for at least 30 minutes. DNA was collected by centrifugation (13,000 rpm, 30 minutes). The pellet was washed twice in 70% ethanol, air-dried, and re-suspended in TE buffer. DNA quality and quantity was confirmed using gel electrophoresis and QuantiFluor dsDNA Sample kit (Promega) as per the manufacturer’s instructions. Whole Genome Sequencing (WGS) DNA was extracted from two whole C57Bl/6J embryos at E10.5 (one male, one female) and six whole Mtrr gt/gt embryos with congenital malformations at E10.5 (four males, two females). Non-degraded gDNA was sent to BGI (Hong Kong) for library preparation and sequencing. The libraries of each embryo were sequenced separately. Sequencing was performed with 150 bp paired-end reads on an Illumina HiSeq X machine. Quality control of reads assessed with FastQC ( http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ). Adapters and low quality bases removed using Trim Galore ( https://www.bioinformatics.babraham.ac.uk/projects/trim galore/). Summary metrics were created across all samples using the MultiQC package ( http://multiqc.info)71 . Sequencing reads were aligned to the C57Bl/6J reference genome (GRCm38, mm10) using BowTie2 with default parameters ( http://bowtie-bio.sourceforge.net/bowtie2/index.shtml)72 . Duplicates were marked using Picard ( http://broadinstitute.github.io/picard ). Structural variant analysis was performed using Manta 73 . Structural variants (SVs) were filtered using vcftools (version 0.1.15) 74 . In order to identify single nucleotide polymorphisms (SNPs), the data was remapped to the mm10 reference mouse genome using BWA (version 0.7.15-r1144-dirty) 75 . Reads were locally realigned and SNPs and short indels identified using GenomeAnalysisTK (GATK, version 3.7) 76 . Homozygous variants were called when more than 90% of reads at the locus supported the variant call, whereas variants with at least 30% of reads supporting the variant call were classified as heterozygous. Two rounds of filtering of variants were performed as follows. Firstly, low quality and biased variant calls were removed. Secondly, variants with: i) simple repeats with a periodicity 8 bp, iii) dinucleotide repeats >14 bp, iv) low mapping quality (3 heterozygous variants fell within a 10 kb region were removed using vcftools (version 0.1.15) as was previously described 77 . The 129P2/OlaHsd mouse genome variation data was downloaded from Mouse Genomes Project 78 . Methylated DNA immunoprecipitation and sequencing (MeDIP-Seq) MeDIP-seq was carried out as described previously 79 . Briefly, 3 µg of sperm gDNA was sonicated using a Diagenode Bioruptor UCD-200 to yield 200-700 bp fragments that were end-repaired and dA-tailed. Illumina adaptors for paired-end sequencing were ligated using the NEB Next DNA Library Prep Master Mix for Illumina kit (New England Biolabs). After each step, the DNA was washed using Agencourt AMPure XP SPRI beads (Beckman Coulter). Immunoprecipitations (IPs) were performed in triplicate using 500 ng of DNA per sample, 1.25 µl of mouse anti-human 5mC antibody (clone 33D3; Eurogentec Ltd., Cat No. BI-MECY, RRID:AB_2616058), and 10 µl of Dynabeads coupled with M-280 sheep anti-mouse IgG bead (Invitrogen). The three IPs were pooled and purified using MinElute PCR Purification columns (Qiagen). Libraries were amplified by PCR (12 cycles) using Phusion High-Fidelity PCR Master Mix and adaptor specific iPCR tag primers ( Supplementary Table 7 ), and purified using Agencourt AMPure XP SPRI beads. The efficiency of the IP was verified using qPCR to compare the enrichment for DNA regions of known methylation status (e.g., methylated in sperm: H19 and Peg3 ICR, Supplementary Fig. 4a ) 49 in the pre-amplification input and the IP fractions. MeDIP library DNA concentrations were estimated using the Kapa Library Quantification kit (Kapa Biosystems) and were further verified by running on an Agilent High Sensitivity DNA chip on an Agilent 2100 BioAnalyzer. Sequencing of MeDIP libraries was performed using 100 bp paired-end reads on an Illumina HiSeq platform at the Babraham Institute Next Generation Sequencing Facility (Cambridge, UK). Quality assessment of the sequencing reads was performed using FastQC ( http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ ). Adaptor trimming was performed using Trim Galore ( http://www.bioinformatics.babraham.ac.uk/projects/trim galore/). Reads were mapped to the GRCm38 (mm10) reference genome using Bowtie2 ( http://bowtie-bio.sourceforge.net/bowtie2/index.shtml ) 72 . All programmes were run with default settings unless otherwise stated. Sample clustering was assessed using principle component analysis (PCA), using the 500 most variable windows with respect to read coverage (as a proxy for methylation) for 5 kb window across all samples. Further data quality checks and differential methylation analysis was performed using the MEDIPS package in R 33 . The following key parameters were defined: BSgenome = BSgenome.Mmusculus.UCSC.mm10, uniq = 1e-3, extend = 300, ws = 500, shift=0. Differentially methylated regions (DMRs) were defined as windows (500 bp) in which there was at least 1.5-fold difference in methylation (reads per kilobase million mapped reads (RPKM)) between C57Bl/6J and Mtrr sperm methylation level with a p-value <0.01. Adjacent windows were merged using BEDTools (version 2.27.0) 80 . The background methylome was defined as all 500 bp windows across the genome at which the sum of the average RPKM per genotype group was >1.0. The genomic localisations of DMRs including association with coding/non-coding regions and CpG islands was determined using annotation downloaded from University of California, Santa Cruz (UCSC) 81 . The percentage of DMRs associated with repetitive regions of the genome was calculated using RepeatMasker software ( http://www.repeatmasker.org ). Enrichment analysis of published ChIP-seq and ATAC-seq data Mean enrichment of specific histone modifications and THSS, CTCF, H3.3, and PRM1 binding in the DMR regions were determined using published data sets including ChIP-seq data in CD1 spermatozoa collected from cauda epididymis 42 , ESCs 35 and TSCs 35 , and ATAC-seq data in CD1 spermatozoa collected from cauda epididymis 42 and B6D2F1 epiblast and extraembryonic ectoderm at E6.5 43 . The source and accession numbers of processed ChIP-seq and ATAC-seq wig/bigwig files are shown in Supplementary Table 8 and accessible on GitHub ( https://github.com/CTR-BFX/Blake_Watson ). To ensure that the analysis was consistent across public data sets, all wig files were converted to bigwig using UCSC tools “wigToBigWig -clip” ( http://hgdownload.soe.ucsc.edu/admin/exe/ ). DMRs identified in sperm from all three Mtrr genotypes (MeDIP-seq analysis) were combined to generate a list of 893 DMRs. To prevent the inclusion of DMRs associated with genomic variation, the 20 Mb region surrounding the Mtrr gene (Chr13:58060780-80060780) that was identified as 129P2Ola/Hsd genomic sequence was masked. This resulted in 459 DMRs for subsequent analysis. The ChIP-seq and ATAC-seq files in sperm 42 were originally aligned to mouse reference genome mm9. The files were converted to mouse reference genome mm10 to match the other published data sets in this analysis using hgLiftOver with the mm9ToMm10.over.chain ( http://genome.ucsc.edu/cgi-bin/hgLiftOver ). To identify the baseline enrichment profiles around the DMRs for specific histone modifications, THSS, CTCF, H3.3, or PRM1, a similar number of genomic regions were randomly selected using bedtools (v2.26.0) 80 with the following command: “bedtools2/2.26.0, bedtools shuffle -i DMRs.bed -g Mus_GRCm38_chrall.fa.fai -chrom -seed 27442958 -noOverlapping -excl Mtrr_mask20Mb.bed”. The DMR profiles were created using deeptools (version 2.3.1) 82 , via computeMatix 3 kb scaled windows, flanking regions of 6 kb, and a bin size of 200 bp, and plotted with plotProfile. Enhancer analysis To determine whether genetic variants or DMRs overlapped with known enhancer regions, FANTOM5 enhancer database 83 for GRCm38 mouse genome ( https://fantom.gsc.riken.jp/5/ ; F5.mm10.enhancers.bed.gz) was used. All .bed files were applied to UCSC Genome Browser 81 to check for region specific features. The distance in base pairs between DMRs and genes or between enhancers and genes was calculated using the closest coordinates (the start/end of DMR or enhancer) to the transcriptional start site (TSS) minus the TSS and then plus 1. To determine further interactions between enhancers and promoters, we analysed public Hi-C data sets 35 for ESC and TSC (E-MTAB-6585; ESC_promoter-other_interactions_GOTHiC.txt and TSC_promoter-other_interactions_GOTHiC.txt) using WashU Epigenome Browser 84 . Quantitative reverse transcription PCR (RT-qPCR) For RNA expression analysis, cDNA was synthesised using RevertAid H Minus reverse transcriptase (Thermo Scientific) and random hexamer primers (Thermo Scientific) using 1-2 µg of RNA in a 20-µl reaction according to manufacturer’s instructions. PCR amplification was conducted using MESA Green qPCR MasterMix Plus for SYBR Assay (Eurogentec Ltd.) on a DNA Engine Opticon2 thermocycler (BioRad). The following cycling conditions were used: 95°C for 10 minutes, 40 cycles: 95°C for 30 seconds, 60°C for 1 minute, followed by melt curve analysis. Transcript levels were normalised to Hprt and/or Gapdh RNA levels. Relative cDNA expression levels were analysed as previously described 85 . Transcript levels in C57Bl/6J tissue were normalized to 1. For primer sequences and concentrations, refer to Supplementary Table 9 . Bisulfite mutagenesis and pyrosequencing Between 250 ng and 2 µg of gDNA extracted from each tissue sample was bisulfite treated with an Imprint DNA Modification Kit (Sigma). Control samples lacking DNA template were run to ensure that there was no contamination during the bisulfite conversion of DNA. To quantify DMR CpG methylation, pyrosequencing was performed. 50 ng of bisulfite-converted DNA was used as template for PCR, together with 0.2 uM of each biotinylated primer and 0.25 units of HotStarTaq PlusDNA Polymerase (Qiagen). Refer to Supplementary Table 10 for primer sequences, which were designed using PyroMark Assay Design Software 2.0 (Qiagen). PCR was performed in triplicate using the following conditions: 95°C for 5 minutes, 40 cycles of 94°C for 30 seconds, 56°C for 30 seconds, 72°C for 55 seconds, and then 72°C for 5 minutes. PCR products were purified using Strepdavidin Sepharose High Performance beads (GE healthcare). The beads bound to DNA were washed in 70% ethanol, 0.4 M NaOH and 10 mM Tris-acetated (pH 7.6) and then hybridized to the sequencing primer in PyroMark annealing buffer (Qiagen) according to the manufacturer’s instructions. Pyrosequencing was conducted using PyroMark Gold reagents kit (Qiagen) on a PyroMark MD pyrosequencer (Biotage). The mean CpG methylation was calculated using three to eight biological replicates and at least two technical replicates. Analysis of methylation status was performed using Pyro Q-CpG software (Biotage). Mass spectrometry Sperm gDNA was digested into individual nucleoside components using the DNA Degradase Plus kit (Zymo Research) according to the manufacturer’s instructions. The heat inactivation step was omitted. 100 ng of degraded DNA per individual was sent to the Babraham Institute Mass Spectrometry Facility (Cambridge, UK), where global cytosine, 5mC and 5-5hmC was determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) as previously described 86 . Sperm of nine males were assessed per genotype and analysed in pools each containing three unique individuals. All pooled samples were analysed in triplicate. Global 5mC and 5hmC levels are reported as percentages relative to C. Western blotting Embryos and placentas at E10.5 were homogenised in lysis buffer (20 mM Tris [pH 7.5], 150 mM NaCl, 1 mM EDTA, 1 mM EGTA, 1% Triton X-100, 2.5 mM sodium pyrophosphate, 1 mM β-glycerolphosphate, 1 mM Na 3 VO 4 and complete mini EDTA-free proteases inhibitor cocktail [Roche Diagnostics]) with Lysing Matrix D ceramic beads (MP Biomedical) using a MagNA Lyser (Roche Diagnostics) at 5,500 rpm for 20 seconds. Samples were incubated on ice for 5 minutes and then homogenized again at 5,500 rpm for 20 seconds. Homogenates were then incubated on ice for 20 minutes with brief intervening vortexing steps occurring every 5 minutes. Samples were then centrifuged at 10,000 x g for 5 minutes. Supernatant from each sample was transferred to a new tube and centrifuged again at 10,000 x g for 5 minutes to ensure that all residual tissue was removed. Protein concentration of tissue lysates was determined using bicinchoninic acid (Sigma-Aldrich). Proteins were denatured with gel loading buffer (50 mM Tris [pH 6.8], 100 mN DTT, 2% SDS, 10% glycerol and trace amount of bromophenol blue) at 70°C for 10 minutes. Equivalent amounts of protein were resolved by 8-10% SDS-PAGE and blotted onto nitrocellulose (0.2 µm, Amersham Protran) with a semi-dry blotter (GE Healthcare). The membrane was stained with Ponceau S solution (Sigma-Aldrich) and the resulting scanned image was used as a loading control. After washing, the membrane was blotted with 5% skimmed milk in Tris buffered saline containing 0.1% Tween-20 (TBS-T) before incubation with 1:1,000 dilution of monoclonal rabbit anti-human HIRA (clone D2A5E, Cell Signalling Technology, Cat. No. 13307, RRID:AB_2798177) overnight at 4°C or 1:10,000 dilution of monoclonal mouse anti-human β-actin (clone AC-74, Sigma-Aldrich, Cat. No. A2228, RRID:AB_476997) for 1 hour at room temperature. Primary antibodies were diluted in TBS-T. The membrane was incubated with 1:10,000 dilution of anti-rabbit IgG conjugated to horse radish peroxidase (HRP; GE Healthcare) diluted in 2.5% skimmed milk in TBS-T or anti-mouse IgG conjugated to HRP (GE Healthcare) diluted in TBS-T. The signal of resolved protein was visualized by Amersham enhanced chemiluminescence (ECL) Western Blotting Analysis System (GE Healthcare) using Amersham Hyperfilm ECL (GE Healthcare). A flat-bed scanner (HP Scanjet G4050) was used to scan films. Band intensities were determined with background subtraction using ImageJ (64-bit) software (NIH, USA). Statistical analysis Statistical analysis was performed using GraphPad Prism software (version 7). RT-qPCR data were analysed by independent unpaired t tests or ordinary one-way ANOVA with Dunnett’s or Sidak’s multiple comparison testing. SV and SNP data were analysed by independent unpaired t tests with Welch’s correction. Bisulfite pyrosequencing data, SV chromosome frequency and DMR distribution at repetitive elements were analysed by two-way ANOVAs with Dunnett’s, Sidak’s or Tukey’s multiple comparisons tests. A binomial test (Wilson/Brown) was used to compare the observed frequency of nucleosome occupancy at DMRs to expected values. Western blot data were analysed using a non-parametric Kruskal-Wallis test with Dunn’s multiple comparisons test. p<0.05 was considered significant unless otherwise stated. DATA AVAILABILITY All relevant data are available from the corresponding author upon reasonable request. WGS data have been deposited in ArrayExpress database at EMBL-EBI under accession number E-MTAB-8513 ( https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-8513 ) and MeDIP-Seq data accession number is E-MTAB-8533 ( https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-8533 ). CODE AVAILABILITY The in-house scripts used for the analysis can be found in the following online repository: https://github.com/CTR-BFX/Blake_Watson . AUTHOR CONTRIBUTIONS G.E.T.B. collected sperm, performed DNA/RNA extractions, generated WGS and MeDIP libraries, and performed RT-qPCR and bisulfite pyrosequencing analyses. G.E.T.B. and E.D.W. dissected tissue and phenotyped conceptuses. G.E.T.B. and E.D.W. collected and analysed the data. X.Z., R.S.H., and G.E.T.B. designed and performed bioinformatics analyses. H.W.Y. performed the western blotting analysis. E.D.W. conceived the project. G.E.T.B., A.C.F.-S., G.J.B., and E.D.W. designed the experiments and interpreted the results. E.D.W. and G.E.T.B. wrote the manuscript. All authors read and revised the manuscript. COMPETING INTERESTS The authors declare no competing interests. SUPPLEMENTARY INFORMATION View this table: View inline View popup Download powerpoint Supplementary Table 1. Common structural variants (SVs)* in all Mtrr gt/gt embryos that were absent in control C57Bl/6J embryos. View this table: View inline View popup Download powerpoint Supplementary Table 2 Characteristics of common small nucleotide polymorphisms (SNPs)* in all Mtrr gt/gt embryos that were absent in control C57Bl/6J embryos. View this table: View inline View popup Download powerpoint Supplementary Table 3 Summary of validation of sperm DMRs by bisulfite pyrosequencing View this table: View inline View popup Download powerpoint Supplementary Table 4 Sperm DMRs identified via MeDIP-seq that were associated with known enhancer regions View this table: View inline View popup Supplementary Table 5 Common sperm DMRs in Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males as determined by MeDIP-seq View this table: View inline View popup Download powerpoint Supplementary Table 6 Characteristics of sperm DMRs from Mtrr +/gt males that were assessed in F1-F2 wildtype somatic tissue. View this table: View inline View popup Download powerpoint Supplementary table 7 iPCR Tag primers used in the MeDIP-seq analysis. View this table: View inline View popup Download powerpoint Supplementary table 8 Source and accession numbers of processed ChIP-seq and ATAC-seq wig/bigwig files View this table: View inline View popup Download powerpoint Supplementary Table 9 PCR primers used in this study. View this table: View inline View popup Supplementary Table 10 Bisulfite pyrosequencing primers used in this study. SUPPLEMENTARY FIGURES AND LEGENDS Download figure Open in new tab Supplementary Figure 1 Transgenerational epigenetic inheritance (TEI) in the Mtrr gt mouse line occurs via the maternal grandparental lineage. a Simplified schematic drawing of one-carbon metabolism. MTRR (red) is a key enzyme at the intersection between folate and methionine pathways that is required to activate methionine synthase (MTR) through the reductive methylation of its vitamin B 12 cofactor. BHMT, betaine-homocysteine S-methyltransferase; CBS, cystathionine beta-synthase; DHF, dihydrofolate; MTHFR, methylenetetrahydrofolate reductase; SAH, S-adenosyl-homocysteine; THF, tetrahydrofolate; TYMS, thymidylate synthase. b-f Highly controlled genetic pedigrees that demonstrated TEI in the Mtrr gt mouse line 11 , some of which are used in this study. Grey shaded boxes, pedigrees that do not display phenotypes at E10.5 in the final generation shown 11 . Pink shaded boxes, pedigrees that display a wide spectrum of phenotypes at E10.5 in the final generation shown 11 . b Mtrr +/gt maternal grandfather pedigree and Mtrr +/gt maternal grandmother pedigree. c Control C57Bl/6J pedigree. d Embryo transfer experiment demonstrating germline inheritance of a yet-to-be determined epigenetic factor to cause congenital malformation at E10.5. F2 wildtype blastocysts derived from an F0 Mtrr +/gt male or female were transferred into control B6D2F1 pseudopregnant females and demonstrated that congenital malformations and not growth phenotypes at E10.5 were independent of the F1 uterine environment 11 . e Mtrr +/gt intercross pedigree. f Mtrr gt/gt intercross pedigree. Pedigree legend: circle, female; square, male; blue outline, C57Bl/6J mouse line; black outline, Mtrr gt mouse line; pink outline, B6D2F1 mouse line; white fill, Mtrr +/+ ; half black-half white fill, Mtrr +/gt ; black fill, Mtrr gt/gt . Download figure Open in new tab Supplementary Figure 2 Frequency and location of genetic variants in C57Bl/6J and Mtrr gt/gt embryos. a, b Whole genome sequencing data showing the average frequency of a structural variants (SVs) and b single nucleotide polymorphisms (SNPs) for each chromosome. Phenotypically normal C57Bl/6J embryos (N=2, black bars) and severely affected Mtrr gt/gt embryos (N=6, blue bars) were assessed. Data is presented as mean ± standard deviation (sd). Note that the gene-trap insertion in the Mtrr locus is on chromosome 13. c, d Genomic location of c SVs and d SNPs in C57Bl/6J and Mtrr gt/gt embryos after masking the region surrounding the gene-trap insertion site. e, f UpsetR plots showing intersections of e SVs or f SNPs between individual C57Bl/6J and Mtrr gt/gt embryos. Arrows indicate the variants that are present in all Mtrr gt/gt embryos and not C57Bl/6J embryos. See also Supplementary Tables 1 and 2. Download figure Open in new tab Supplementary Figure 3 Confirmation of spermatozoa purity and validation of immunoprecipitation. a Bisulphite pyrosequencing of imprinting control regions in DNA from spermatozoa collected from cauda epididymides to determine sperm purity. Percentage methylation at specific CpG sites in the maternally imprinted Peg3 differentially methylated region (DMR) and paternally imprinted H19 DMR were determined in sperm samples isolated from C57Bl/6J (black circles), wildtype ( Mtrr +/+ ; purple circles), Mtrr +/gt (green circles) and Mtrr gt/gt (blue circles) mice. C57Bl/6J liver (grey dots) was assessed as a control. Data is represented as mean ± standard deviation (sd) for each CpG site. N=8 males per group. b Percentage recovery of DNA input after MeDIP experiment as determined using RT-qPCR to amplify known methylated ( Nanog and H19 ) and unmethylated ( H1t and TsH2B ) regions. MeDIP samples from sperm of C57Bl/6J (black bars), Mtrr +/+ (purple bars), Mtrr +/gt (green bars), and Mtrr gt/gt (blue bars) males are shown. Each bar indicates one individual (N=8 males per genotype). Download figure Open in new tab Supplementary Figure 4 Validation of a panel of sperm DMRs identified in Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males. a-c Validation of differentially methylated regions (DMRs) identified in a MeDIP-seq experiment of sperm from wildtype ( Mtrr +/+ ; purple circles), Mtrr +/gt (green circles) and Mtrr gt/gt (blue circles) males relative to C57Bl/6J control sperm (black circles). The average percentage methylation at individual CpG sites was determined by bisulfite pyrosequencing. Data is plotted as mean ± standard deviation (sd) at each CpG site. N=8 males per group (four samples from MeDIP-seq analysis plus four unique samples). The coordinates for each DMR are given. Two-way ANOVA, with Sidak’s multiple comparisons test, performed on mean methylation per CpG site per genotype group. ***p<0.001. Download figure Open in new tab Supplementary Figure 5 Chromosomal distribution of DMRs in sperm of Mtrr males. a-d Phenograms showing chromosomal location of sperm DMRs (black rectangles) identified via MeDIP-seq analysis in a wildtype ( Mtrr +/+ ), b Mtrr +/gt , and c Mtrr gt/gt males compared to C57Bl/6J sperm. Red box indicates region on chromosome 13 surrounding Mtrr locus identified in Fig. 1a . d A phenogram depicting the chromosome location of the 54 common sperm DMRs between Mtrr genotypes when compared to C57Bl/6J sperm. e Relative genomic distribution of methylated regions among the 54 common sperm DMRs between Mtrr +/+ , Mtrr +/gt and Mtrr gt/gt males (compared to C57Bl/6 males) with respect to unique sequences and repetitive elements, coding and non-coding regions, and CpG islands (CGIs), shores and shelves. N=8 males per group. Download figure Open in new tab Supplementary Fig. 6 General epigenetic signature of genomic regions identified as sperm DMRs in Mtrr males. a Using published ChIP-seq data sets in wildtype CD1 spermatozoa 5 , mean enrichment of selected histone modifications and DNA binding proteins was determined in the genomic regions identified as differentially methylated in sperm. Differentially methylated regions (DMRs) of all Mtrr genotypes, excluding those within the 20 Mb region surrounding the Mtrr locus, were combined in this analysis (N= 379 DMRs; red line) and compared to the baseline genome (blue line; see Methods). b, c Using published ATAC-seq data sets in b wildtype CD1 spermatozoa 5 and c wildtype B6D2F1 mouse epiblast and extraembryonic ectoderm (ExE) at embryonic day 6.5 6 , mean enrichment of Tn5 transposase sensitive site (THSS) was determined in sperm DMRs of all Mtrr genotypes combined (N= 379 DMRs; red line) compared to the baseline genome (blue line). DMRs in the region surrounding the Mtrr gene-trap insertion site were masked in both analyses. Dotted lines indicate the start and end of the DMR. Six kilobases (Kb) of DNA surrounding the DMR was also considered. Download figure Open in new tab Supplementary Figure 7 Analysis of DNA methylation and gene expression at sperm DMRs in Mtrr gt/gt tissue. a-j Schematic drawings of differentially methylated regions (DMRs; blue rectangle) identified in Mtrr +/gt sperm in relation to the closest gene alongside bisulfite pyrosequencing analysis of CpG methylation at these DMRs in C57Bl/6J control (black circles) and Mtrr gt/gt (blue circles) phenotypically normal embryos and placentas at E10.5. The average percentage of methylation at individual CpG sites within the corresponding DMR is shown (mean ± standard deviation (sd) for each CpG site). Enhancer (Enh) overlap is shown in red. N=4 placentas and N=6-8 embryos assessed per experimental group. Two-way ANOVA, with Sidak’s multiple comparisons test, performed on mean methylation per CpG site per genotype group. *p<0.05, **p<0.01, ***p<0.001. k-m RT-qPCR analysis of mRNA expression of some of the genes proximal to or overlapping with sperm DMRs (shown in a-f). Gene expression was assessed in C57Bl/6J control (black bars) and Mtrr gt/gt (blue and white bars) k embryos and l placentas at E10.5, and m Mtrr gt/gt adult livers. N=4-8 individuals per experimental group. Tissue from phenotypically normal (blue bars) and severely affected (white bars) Mtrr gt/gt conceptuses was assessed. Expression data is plotted as mean ± sd, and relative to C57Bl/6J levels (normalized to 1). Independent t tests or one-way ANOVA with Dunnett’s multiple comparisons tests were performed. *p<0.05, **p<0.01, ***p<0.001. Download figure Open in new tab Supplementary Figure 8 Epigenetic signature of the intragenic Cwc27 DMR in wildtype mouse ESCs and TSCs. Enrichment of DNA binding proteins (CTCF) and histone modifications (H3K27ac, H3K27me3, H3K4me1, H3K4me3, H3K9me3) in the Cwc27 locus on chromosome (Chr) 13 (∼37,000 kb downstream of Mtrr gene) using published ChIP-seq data sets 4 in wildtype embryonic stem cells (ESCs) and trophoblast stem cells (TSCs). Grey rectangles indicate enriched peaks for each histone mark. Red rectangle and grey shading indicate Cwc27 differentially methylated region (DMR) identified in sperm of Mtrr +/gt males. Green rectangles indicate enhancer regions. Partial schematic of protein encoding Cwc27 transcript is shown. Download figure Open in new tab Supplementary Figure 9 Epigenetic signature of the intragenic Tshz3 DMR in wildtype ESCs and TSCs. Enrichment of DNA binding proteins (CTCF) and histone modifications (H3K27ac, H3K27me3, H3K4me1, H3K4me3, H3K9me3) in the Tshz3 locus on chromosome (Chr) 7 using published ChIP-seq data sets 4 in wildtype embryonic stem cells (ESCs) and trophoblast stem cells (TSCs). Grey rectangles indicate enriched peaks for each histone mark. Red rectangle and grey shading indicate Tshz3 differentially methylated region (DMR) identified in sperm of Mtrr +/gt males. Blue rectangles indicate CpG islands. Green rectangle indicates enhancer regions. Schematic of protein encoding Tshz3 transcript is shown. Download figure Open in new tab Supplementary Figure 10 Analysis of Hira DMR methylation and HIRA protein expression. a-c Bisulfite pyrosequencing analysis of average percentage methylation at individual CpG sites in the Hira DMR (see Fig. 5 ) in C57Bl/6J embryos (N=6-8 embryos; black circles) at E10.5 compared to the following: a F3 wildtype ( Mtrr +/+ ) embryos (em) at E10.5 derived from F0 Mtrr +/gt males (N=4 phenotypically normal (n) embryos teal circles; N=3 severely affected (sa) embryos, turquoise circles), b F1 wildtype embryos at E10.5 derived from F0 Mtrr +/gt females (N=7 phenotypically normal (n) embryos, orange circles; N=3 severely affected (sa) embryos, green circles). c F2 wildtype embryos at E10.5 derived from F0 Mtrr +/gt females (N=5 phenotypically normal (n) embryos, purple circles; N=4 severely affected (sa) embryos, pink circles). Data is presented as average methylation (± standard deviation (sd)) per CpG site. Two-way ANOVA, with Sidak’s multiple comparisons test, performed on mean methylation per CpG site. d RT-qPCR analysis of Hira lncRNA expression (striped bars, primer set 2) in embryos (N=6-8) and placentas (N=5-8) from C57Bl/6J (black bars) and Mtrr gt/gt conceptuses (blue bars). Independent t test, **p<0.01. e, f Western blot analysis of HIRA protein in C57Bl/6 (black bars) and Mtrr gt/gt (blue bars) embryos (N=4-8) and placentas (N=5-10) at E10.5. Blots are shown in f. HIRA protein levels were normalised to β-actin loading control. Independent t test, *p<0.05, **p<0.01. ACKNOWLEDGEMENTS We thank Drs Nozomi Takahashi and Tessa Bertozzi for their technical support, Dr Claire Senner for critical discussion, and Drs Jamie Hackett and Miguel Branco for .bed files. The MeDIP-seq and LC-MS/MS was performed at the Babraham Institute (UK). WGS was performed by BGI (Hong Kong). This work was funded by grants from Lister Institute for Preventative Medicine and the Centre for Trophoblast Research (CTR) to E.D.W and from the MRC MR/J001597 and Wellcome Trust WT095606 (to A.C.F.-S). The following support was provided: Wellcome Trust 4-year DTP in Developmental Mechanisms (to G.E.T.B.) and CTR funding (to G.E.T.B., H.W.Y., X.Z., R.S.H.). Footnotes The text was clarified throughout the revised manuscript. Figures 2, 5 and 6 revised; Supplementary figures 1, 2, 5, 8, 9, 10 revised; Supplementary tables 1-10 were added. https://github.com/CTR-BFX/Blake_Watson REFERENCES 1. ↵ Chen , Q. et al. Sperm tsRNAs contribute to intergenerational inheritance of an acquired metabolic disorder . Science 351 , 397 – 400 ( 2016 ). OpenUrl Abstract / FREE Full Text 2. ↵ Gapp , K. et al. Implication of sperm RNAs in transgenerational inheritance of the effects of early trauma in mice . Nat Neurosci 17 , 667 – 9 ( 2014 ). OpenUrl CrossRef PubMed 3. ↵ Padmanabhan , N. et al. 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Mutation in folate metabolism causes epigenetic instability and transgenerational effects on development . Cell 155 , 81 – 93 ( 2013 ). OpenUrl CrossRef PubMed Back to top Previous Next Posted December 20, 2020. Download PDF Data/Code Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Defective folate metabolism causes germline epigenetic instability and distinguishes Hira as a phenotype inheritance biomarker Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Defective folate metabolism causes germline epigenetic instability and distinguishes Hira as a phenotype inheritance biomarker Georgina E.T. Blake , Xiaohui Zhao , Hong wa Yung , Graham J. Burton , Anne C. Ferguson-Smith , Russell S. Hamilton , Erica D. Watson bioRxiv 2020.05.21.109256; doi: https://doi.org/10.1101/2020.05.21.109256 Share This Article: Copy Citation Tools Defective folate metabolism causes germline epigenetic instability and distinguishes Hira as a phenotype inheritance biomarker Georgina E.T. Blake , Xiaohui Zhao , Hong wa Yung , Graham J. Burton , Anne C. Ferguson-Smith , Russell S. Hamilton , Erica D. 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