EpiGenie | Epigenetics, Stem Cell, and Synthetic Biology News http://epigenie.com Scientific News, Technology, and Product Information Wed, 16 May 2018 19:20:09 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.6 Sea Snails Thank RNA-induced DNA Methylation for the Long-term Memories! http://epigenie.com/sea-snails-thank-rna-induced-dna-methylation-long-term-memories/ http://epigenie.com/sea-snails-thank-rna-induced-dna-methylation-long-term-memories/#respond Wed, 16 May 2018 17:35:04 +0000 http://epigenie.com/?p=27040 Forget everything you know about memories (!) because a new study has turned our knowledge regarding memory formation on its head by showing the ability to transfer memories from animal-to-animal!

Current dogma states that learning-induced modifications of synaptic connections underlie the storage of our long-term memory (LTM); however, recent studies have suggested that neuron cell bodies store LTM in some unidentified manner (See Chen et al., 2014, Johansson et al., 2014, and Ryan et al., 2015). This led researchers from the group of David L. Glanzman (University of California, Los Angeles, USA) to study the formation of LTM in the Aplysia californica sea snail (or Californian sea hare) and they now propose that, incredibly, RNA-induced DNA methylation can encode LTM.

Researchers employ Aplysia californica as a model animal to study the cellular basis of learning and memory because of the simplicity and large size of the neural circuitry. Bédécarrats and colleagues employed the Aplysia gill and siphon withdrawal reflex  (shocking stuff indeed!) to study how long-term sensitization training led to the formation of non-associative LTM by assessing the significance of RNA extracted from the Aplysia central nervous system (CNS).

Here are the memorable results from this unforgettable new sea snail study into long-term memory:

  • RNA extracted from the CNS of animals that undergo long-term sensitization training induces a reflex enhancement when injected into untrained animals
  • Application of a DNA methyltransferase inhibitor (RG-108) demonstrated that both RNA-induced and training-induced sensitization requires DNA methylation
    • These data support a model by which RNA-induced DNA methylation encodes LTM
  • Sensory neuron hyperexcitability underlies sensitization in sea snails, and the authors discovered that treatment with RNA from trained animals selectively increases excitability in ex vivo cultures of sensory neurons, but not in motor neurons, from untrained animals

The talented team hopes to continue their research in sea snails and discover which specific RNA species mediate non-associative LTM transfer (non-coding and long non-coding RNAs are top of the list!) and the transport mechanisms employed to transfer RNA to Aplysia neurons (exosomes or extra-cellular vesicles?). Furthermore, assays of the genomic targets of the RNA-induced DNA methylation may also help to further our understanding of this incredible process.

Senior author David L. Glanzman shares, “It’s as though we transferred the memory. If memories were stored at synapses, there is no way our experiment would have worked. I think in the not-too-distant future, we could potentially use RNA to ameliorate the effects of Alzheimer’s disease or post-traumatic stress disorder.”

Will this new research move us closer to transplanting our memories? To find out, see all the unforgettable details at eNeuro, May 2018.

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C. elegans Histone Memory of a Tropical Vacation http://epigenie.com/c-elegans-histone-memory-tropical-vacation/ http://epigenie.com/c-elegans-histone-memory-tropical-vacation/#respond Tue, 15 May 2018 03:27:05 +0000 http://epigenie.com/?p=27033 Most of us wouldn’t mind taking a tropical vacation, and we’re all likely to snap a few selfies to capture vacation memories. While the humble Caenorhabditis elegans may lack the latest phone and accompanying selfie stick, it makes up for it with epigenetic memory of warm weather vacations. More specifically, worms raised at higher temperatures undergo epigenetic changes which are retained in future generations—even when moved back to lower temperatures.

Rather than taking a vacation, researchers from the labs of Ben Lehner (European Molecular Biology Laboratory) and Tanya Vavouri (Josep Carreras Leukaemia Research Institute) have been hard at work investigating transgenerational epigenetic inheritance. Their recent work has uncovered the transmission of environmentally induced epigenetic changes that persist for 14 generations in C. elegans.

The talented team took C. elegans and integrated a multicopy transgene coding for a fluorescent protein. The transgene was put under the control of the daf-21 promoter (hsp90) so that increased temperature would drive expression. The worms were then subjected to a Bahamas-worthy 25oC for five consecutive generations. Subsequent generations of worms were raised at 20oC, and expression from the transgene was assessed:

  • Expression of the transgene was elevated for 14 generations after the return to 20oC
  • Worms whose ancestors were grown at higher temperatures exhibit differential histone modification
    • Progeny have decreased trimethylation on histone 3, lysine 9 (H3K9me3)—a modification associated with repression
  • SET-25 is the methyltransferase responsible for H3K9 trimethylation, and is required for repression at low temperatures
    • Inactivation of set-25­­resulted in increased expression of the transgene—expression was equivalent in worms raised at either 20oC or 25oC
  • For endogenous loci, repetitive elements and pseudogenes were most affected by SET-25 derepression
    • Although changes in endogenous protein-coding genes were minor, they were detectable for three generations after being returned to the low-temperature environment

Thus, it appears that high temperature (25oC) inhibits the SET-25 pathway, leading to loss of methylation at H3K9, resulting in increased expression from the transgene array. This change in chromatin state is transmitted to progeny, resulting in an epigenetic “memory” of the high-temperature environment. The repression is restored via heterochromatin remodeling during normal cell division through subsequent generations.

Co-senior author Ben Lehner shares, “We discovered this phenomenon by chance, but it shows that it’s certainly possible to transmit information about the environment down the generations.” First author Adam Klosin adds, “We don’t know exactly why this happens, but it might be a form of biological forward-planning.” Co-senior author Tanya Vavouri concludes, “Worms are very short-lived, so perhaps they are transmitting memories of past conditions to help their descendants predict what their environment might be like in the future.”

Although the inheritance of epigenetic alterations is not a new phenomenon, the persistence over 14 generations raises new questions about the potential duration of epigenetic inheritance. Just to be safe, for the sake of your great-great-grandchildren, go ahead and take a tropical vacation.

Take a tropical vacation over at Science, 2017

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Snord116 Keeps DNA Methylation’s Circadian Rhythm Ticking in the Brain http://epigenie.com/snord116-keeps-dna-methylations-circadian-rhythm-ticking-brain/ http://epigenie.com/snord116-keeps-dna-methylations-circadian-rhythm-ticking-brain/#respond Thu, 10 May 2018 16:42:57 +0000 http://epigenie.com/?p=27028 Sunrise, Sunset. The tempo of a day can quickly pass us by while filling our brain with all epigenetics has to offer. But whether our brains are aware of it or not, with each sunrise and sunset comes a rhythmic genome-wide DNA methylation profile.

To gain insight into exactly what makes our brain’s rhythmically tick, the lab of Janine LaSalle at the University of California, Davis, utilized a Snord116 deletion mouse model of Prader-Willi syndrome (PWS). PWS and Angelman syndrome (AS) are reciprocal imprinting disorders that arise from aberrations of the SNRPN-UBE3A locus, with AS caused by a loss of maternal UBE3A and PWS by a loss of the paternal SNORD116 cluster. Notably, these two disorders produce distinct neurodevelopmental profiles characterized by sleep and metabolic problems.

Here’s what the group found in the brain’s cortex when they compared adult male Snord116+/− mice to matched wild-type controls across six different time points on the clock:

  • Whole-genome bisulfite sequencing (WGBS) of wild type cortex revealed cycling of >4,000 differentially methylated regions (DMRs), which are comprised of >23,000 CpGs!
    • However, PWS mice display a loss or a shift in rhythmicity at the majority of these DMRs
    • Rhythmic DMRs belong to genes with functions related to body-weight and metabolism, where disruption of these traits represent hallmarks of PWS and AS
    • The genes identified display a strong overlap with differentially methylated genes in the brains of PWS patients as well as another study of circadian rhythm in humans
    • Integration with previous RNA-seq data revealed a time-lagged relationship between the cycling of DNA methylation and transcription
    • Both WGBS and RNA-seq revealed cross-talk with the only other locus containing imprinted clusters snoRNAs (Dlk1-Dio3), which results in reciprocal disorders known as Temple and Kagami-Ogata syndromes (TS and KOS)
    • DNA fluorescence in situ hybridization (FISH) demonstrated that Snord116 modifies the unique allele-specific chromatin decondensation occurring at these imprinted loci

Clocking In With the Time Keepers

First author Rochelle Coulson shares, “DNA methylation is dynamic. Far more so than has historically been appreciated. We found a unique set of CpGs that are rhythmically methylated across diurnal time in wildtype mouse cortex, and this pattern is disrupted by the loss of Snord116, a long noncoding RNA from the PWS locus. These rhythmic CpGs are not randomly scattered throughout the genome, but are clustered into specific regions important for gene regulation, and we were surprised at how well conserved these sites were between mouse and human. They also linked the PWS locus to another imprinted locus, strengthening the imprinted gene network we’ve started to see come up again and again. Sleep difficulties are a common feature of neurological disorders, and Prader-Willi syndrome is no exception. The co-regulatory networks between sleep, metabolism and imprinted loci suggest that understanding the disrupted epigenetic rhythms in PWS may hold promise for the future application of chronotherapy in the treatment of a wide variety of neurodevelopmental, neuropsychiatric, metabolic, sleep, and imprinted disorders.”

Senior author Janine LaSalle concludes, “We were pleasantly surprised by several findings in this study. First, that there were significant rhythmic methylation dynamics in the cortex. Less than 1% of possible CpGs were rhythmic, so it’s not as though the whole methylome is getting erased and re-established while we sleep, but still enough to be important and relevant. Second, that loss of a single imprinted noncoding RNA locus was required for the proper rhythmicity of 97% of these methylation sites. Third, that there was a strong overlap in both of these effects between mouse and human. Fourth, that the identified genes highlighted functions in circadian entrainment and body weight, relevant to PWS. The whole study was a remarkable demonstration of a time by genotype interaction in brain. I now like to think that “time is the new sex” as important biological variables to consider in neuroscience and genetics.”

Clock in to the brains epigenome over at Nature Communications, April 2018

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EpiTOF Histone Modification Analysis Reveals How Aging Cells Grow Apart! http://epigenie.com/epitof-histone-modification-analysis-reveals-aging-cells-grow-apart/ http://epigenie.com/epitof-histone-modification-analysis-reveals-aging-cells-grow-apart/#respond Wed, 09 May 2018 20:09:36 +0000 http://epigenie.com/?p=27025 Some say that all babies look the same – small, warm bags of tears and mayhem – with significant differences only appearing as we grow older and grow apart from our newborn brethren (and sistren!). Our burgeoning epigenome may react to aging in a very similar manner, with age-related losses and gains of DNA methylation combining to create widespread variation in CpG methylation. However, we know less regarding how the levels of histone modifications vary with age.

Researchers from the laboratories of Paul J. Utz, Purvesh Khatri, and Alex J. Kuo (Stanford University, USA) knew that the high-throughput study of histone modifications in single cells represented a difficult task. To overcome this technological obstacle, the team put their differences aside to create EpiTOF (or epigenetic landscape profiling using cytometry by time-of-­flight) to measure variations in the levels of eight classes of histone modifications and four histone variants in twenty-two major types of human immune cells.

In their latest study, the talented team now reports on how their highly multiplexed mass cytometry analysis has aided the understanding of the profound impact of aging on the chromatin landscape.

Here are the highlights from this fantastic new study:

  • Distinct histone modification profiles characterize immune cell subtypes of the healthy human immune system
    • Cell-type-specific profiles indicate the hematopoietic lineages from which individual populations derive
    • ChIP-Seq analysis indicates drastic changes to profiles associated with gene expression reprogramming during hematopoietic lineage determination
    • Overall, unique single-cell profiles form a molecular signature that predicts immune cell identity, including T cell functional subsets
  • Comparisons between young and old cells demonstrated that levels of a wide range of histone modification increase in diverse immune cell types with age
    • Importantly, an increase in cell-to-cell variability in histone modification profiles within each immune cell subtype represents a molecular signature of aging
    • Elevated epigenomic “noise” derived from increased polycomb repressive complex-mediated H3K27me3 deposition leads to varying histone modification profiles in single cells and higher transcriptional noise during aging
  • Finally, twin cohort analysis suggested that non-heritable influences majorly drive aging-related variations in histone modification profiles (~70%) and demonstrate that profile divergence widens with age

Taken together, the findings from this new technological breakthrough highlights the profound impact of aging on histone modification at the single cell level, suggesting that while our cells may begin in a similar state, they soon grow apart as we age (disgracefully or not!). Next, the authors hope to apply EpiTOF to identify histone modifications dysregulated in immune-mediated diseases and cancer to facilitate the development of therapeutic agents targeting histone-modifying enzymes.

For all the details on EpiTOF and more on how out chromatin landscape changes with age, see Cell, March 2018.

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Intergenerational Transmission of Dad’s Diet: Dnmt2 Provides a Big Payload of Small RNAs http://epigenie.com/intergenerational-transmission-dads-diet-dnmt2-provides-big-payload-small-rnas/ http://epigenie.com/intergenerational-transmission-dads-diet-dnmt2-provides-big-payload-small-rnas/#respond Fri, 04 May 2018 16:20:00 +0000 http://epigenie.com/?p=27017 Dnmt2 represents the lesser-known child of the DNA-methyltransferase family, but not because of any lack of pizazz or stage presence, but perhaps due to the lack of detectable DNA-cytosine methylation activity when compared to its more well-known brethren (Dnmt1 and Dnmt3). Instead of modifying DNA, Dnmt2 plays a big role in transfer RNA (tRNA) methylation to promote tRNA folding and structural stability and the modulation of chemical and biological properties. Now, new findings describe a role for Dnmt2 in shaping sperm RNA profiles.

Small non-coding RNAs (sncRNAs) in sperm (including tRNAs) represent crucial mediators of intergenerational effects, such as those related to paternal exercise and diet. However, the mechanisms how these mobile, trans-acting sperm sncRNAs encode this paternal information remained unclear until the publication of a new study from the laboratory of Qi Chen (University of Nevada, Reno, USA).

To gain insight into the intergenerational transmission of paternally acquired metabolic disorders the talented team employed Dnmt2-/- and Dnmt2+/+ male mice fed a high-fat diet (HFD = 60% fat, which led to obesity, glucose intolerance, and insulin resistance) or a normal diet (10% fat, not associated with metabolic disease) from 6 weeks to 6 months of age.

Here is all the big news about Dnmt2 and sperm small non-coding RNAs:

  • Mice lacking Dnmt2 do not exhibit sperm sncRNA-mediated transmission of HFD-induced metabolic disorders to offspring
    • Analysis of 13 different RNA modifications highlighted a lack of 5-methylcytosine (m5C) and 2-methylguanine (m2G) deposition in HFD-induced sperm sncRNAs in the absence of Dnmt2
  • Interestingly, the lack of Dnmt2 activity also modulates the expression profile of sperm tRNA-derived small RNAs and rRNA-derived small RNAs
    • The authors posit that the totality of sncRNAs and their modifications compose a sperm RNA “coding signature” required for paternal epigenetic memory
  • The authors discovered that Dnmt2-mediated m5C deposition affects the secondary structure and biological properties of sncRNAs
    • Therefore, sperm RNA modifications may represent an additional layer of paternal hereditary information

The authors of this fascinating new study suggest that a combination of sperm sncRNA types and modifications may interact with other RNA species to generate multiple synergistic effects during early embryo development. Moving forward, the team aims to discover just how Dnmt2 responds to the parental environment and encodes the sperm sncRNA signature.

For more on the big impact on Dnmt2 on sperm small RNAs, head over to Nature Cell Biology, 2018.

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Two Barcodes, One DNA Fragment: Budget-Friendly Single-Cell Whole-Genome Bisulfite Sequencing http://epigenie.com/two-barcodes-one-dna-fragment-budget-friendly-single-cell-whole-genome-bisulfite-sequencing/ http://epigenie.com/two-barcodes-one-dna-fragment-budget-friendly-single-cell-whole-genome-bisulfite-sequencing/#respond Sun, 29 Apr 2018 15:15:09 +0000 http://epigenie.com/?p=26996 While single-cell whole-genome bisulfite sequencing is rapidly evolving, the associated price tag hasn’t been quite as dynamic. This lack of dynamism is primarily because current single-cell whole-genome bisulfite sequencing (scWGBS) methods are limited by the need to process each cell in individual reaction vessels and also low alignment rates. These limitations mean a high (financial) price needs to be paid to get enough information from single cells. But now, the lab of Andrew Adey at Oregon Health & Science University (USA) has slashed costs and brings forth single-cell combinatorial indexing for methylation analysis (sci-MET).

The talented team’s new sci-MET method employs their combinatorial indexing strategy that was previously applied to other DNA, RNA, and chromatin accessibility sequencing methods. A combinatorial indexing strategy eliminates the need for single-cell reaction vessels by employing two unique barcodes to tag each cell’s DNA and keep track of the single-cell it was derived from during later pooling steps.

Here’s how this new approach works:

  1. Cell/Nuclei preparation:
    1. Cells are dissociated
    2. Nuclei are isolated, and nucleosomes are depleted
  2. Tagmentation:
    1. Fluorescence activated nuclei sorting (FANS) is used to collect between 1 to 2000 nuclei per a well
    2. A transposase tags the DNA with adaptors that are depleted of cytosine and thus will not be converted by subsequent bisulfite treatment
  3. scWGBS library preparation:
    1. The samples from all wells are pooled
    2. FANS is used to redistribute the samples, where there are 22 nuclei per well
      1. Each nuclei has a unique transposase barcode from the tagmentation step
    3. The DNA is bisulfite converted
    4. Random priming is used to amplify the libraries and add on the second sequencing adaptor
  4. scWGBS:
    1. The samples are pooled, cleaned, and sequenced

The team then put sci-MET through its paces with a few interesting experiments:

  • They applied sci-MET to a pure human cell population (GM12878) and found that the results closely matches the expected methylation profile
  • They also applied sci-MET to a mix of three human cell lines (GM12878, HEK293, and primary inguinal fibroblast), where they:
    • Achieved read alignment rates of 68 ± 8%, a figure comparable to bulk WGBS and a big step forward for scWGBS
    • Demonstrated that sci-MET discriminates cell types from mixed populations
  • Moving in vivo, the authors applied sci-MET to brain tissue (primary cortical tissue) from three mice, where it was able to discriminate clusters of cell types (excitatory neurons, inhibitory neurons, and non-neuronal) based on CG and CH (non-CpG) methylation
    • A comparison to cortical differentially methylated regions (DMRs) identified by a different single-nuclei WGBS study revealed distinct enrichment in the neuronal clusters for different sets of excitatory and inhibitory DMRs, allowing them to further classify their sets of neuronal clusters into cell populations
  • Overall, the team generated 3,282 single-cell libraries with sci-MET

Senior author Andrew Adey shares, “We can profile thousands of cells simultaneously. This technology reduces the cost to prepare single-cell DNA methylation libraries to less than 50 cents per cell from $20 to $50 per cell. It will be incredibly valuable in any environment where there is cell type heterogeneity. The major areas of interest will be cancer and neuroscience, but we are also applying it to cardiovascular disease.”

Learn how to get the most out of your single-cell budget over at Nature Biotechnology, April 2018

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TERRA lncRNA Tailors a Trimethylation Trio at Telomeres http://epigenie.com/terra-lncrna-tailors-trimethylation-trio-telomeres/ http://epigenie.com/terra-lncrna-tailors-trimethylation-trio-telomeres/#respond Fri, 27 Apr 2018 12:21:17 +0000 http://epigenie.com/?p=26993 A good tailor will make any scientist look presentable in an expensive suit or a glitzy dress (when we escape the confines of a lab coat) and now, the group of Maria A. Blasco (CNIO, Madrid, Spain) describes how long non-coding RNAs (lncRNAs) tailor our telomeric DNA with just enough trimethylated histones to suit any catwalk or red carpet!

The lncRNAs in question, the TERRAs (telomeric repeat-containing RNAs), don´t derive from the bespoke garment-makers of Saville Row in London, but instead mainly arise from a single subtelomeric locus within the long arm of human chromosome 20. Multiple studies have implicated the telomere binding capabilities of TERRAs with various telomere maintenance-related functions, including heterochromatin formation and a previous study from the Blasco lab described a loss-of-function TERRA model (20q-TERRA knockout cells); a system tailor-made to delineate the exact mechanisms linking TERRA to heterochromatin formation at the telomeres.

Now, Montero and colleagues dazzle us with an array of bold colors, stark lines, and new findings that would surely wow any fashionista from Milan to Tokyo. Here is a taste of what they discovered:

  • CRISPR-Cas9 mediated KO of 20q-TERRAs in human osteosarcoma cells inhibits the establishment of a trio of heterochromatin-associated trimethylated histones (H3K9me3, H4K20me3, and H3K27me3) at telomeric regions
    • Furthermore, cells lacking TERRA expression also display shorter telomeres than control cells
  • In normal cells, TERRA binds to the EZH2 (H3K27me3) and SUZ12 (H3K27me3 and H3K27me3) histone methyltransferases and brings the EZH2/SUZ12-containing Polycomb Repressive Complex 2 (PRC2) to telomeres
    • PRC2 then catalyzes the deposition of the facultative heterochromatin-associated H3K27me3 modification
    • The H3K27me3 modification then permits the establishment of the H3K9me3 and H4K20me3 modifications and promotes HP1 binding at telomeres
  • However, the authors did not uncover a close relationship between TERRA status and telomeric- and global-DNA methylation levels

Overall, this stylish new study suggests that TERRA lncRNAs and PRC2 play a crucial role in creating the heterochromatin landscape at telomeric regions.

Do these new research findings “suit” you? To find out, read the full details of this exquisitely tailored study over at Nature Communications, April 2018.

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Transposons and DNA Methylation Learn to Get Along http://epigenie.com/transposons-dna-methylation-learn-get-along/ http://epigenie.com/transposons-dna-methylation-learn-get-along/#respond Fri, 27 Apr 2018 00:47:48 +0000 http://epigenie.com/?p=26988 A lot of things just don’t mix well, dogs and cats, oil and water, and as most geneticists would agree, transposons and DNA methylation. DNA methylation is the mortal enemy of transposon activity; across the tree of life it has a conserved role silencing transposable elements from plants, to algae, to vertebrates. This suggests DNA methylation may have originally evolved in eukaryotes to silence transposable elements. But a recent study suggests that DNA methylation was sought after by some retrotransposons in distantly related eukaryotes. DNA methyltransferases (DNMTs) are ancient, some going back to the last common ancestor. In most species, DNMTs and transposons were engaged in an evolutionary arms race, with transposons finding ways to escape methylation. However, some species have a very odd relationship between the two which challenges our assumptions about this arms race.

Ryan Lister’s lab from The University of Western Australia followed up on a peculiar finding regarding transposable elements and DNMTs. Previous studies showed that DNMTs were counterintuitively linked to reverse transcriptase domains in certain eukaryotes. This may represent a novel mechanism by which transposons escape DNA methylation, or actually use it to their benefit. To interrogate this possible mechanism, the talented team sought out to characterise how cytosine-specific DNMTs have been incorporated into distinct classes of retrotransposons independently across evolution. They used eukaryotic species encoding a high number of DNMTs: the dinoflagellates (phylum including marine plankton species) and charophytes (division including green algae species). The talented team used RNA-seq, whole genome sequencing, and MethylC-seq to annotate and characterize these species genomes. Here’s what they found:

  • RNA-seq uncovered that a large number of less characterized Dnmts (Dnmt5, Dnmt6, and Dntm2) are the only expressed DNMT transcripts across dinoflagellates
    • These strange transcripts also happen to only contain a DNMT domain
  • RNA-seq guided genome annotation revealed that the dinoflagellate species Symbiodinium kawagutii has hundreds of evolutionarily old, and active Dnmts in retrotransposons.
    • Using MethylC-seq, they found that Symbiodinium also has a distinct epigenome among algae and plants, with widespread non-specific hemi-methylated CpGs
    • This may suggest a complex, co-adaptive evolutionary relationship
  • CpG methylation in Symbiodinium is not correlated with gene expression, and is present at active promoters
  • Charophytes independently evolved the incorporation of DNMTs into the coding regions of very different retrotransposon classes
  • Using methylation induction experiments, the authors cloned and expressed the transposon DNMTs to reveal that the retrotransposon DNMTs are active and can de novo methylate CpGs, suggesting that retrotransposons could self-methylate retrotranscribed DNA

This study shows that retrotransposons recruited host DNMT genes in two distantly related eukaryotes. The nearly ubiquitous CpG methylation in Symbiodinium could explain why the functions of DNA methylation is mostly lost in this lineage. The function of the retrotransposon DNMTs is still unclear, but it may be involved in methylation of the retrotranscribed cDNA. This methylated cDNA would then resemble the highly methylated host genome which might allow it to escape being recognised as exogenous. Overall, these findings challenge our long-held view of transposons and DNA methylation as opponents. Their relationship may be much more complex and could change our view of the evolution and function of the epigenome as a whole. Even cats and dogs can get along … if it’s evolutionarily advantageous.

Read more about this evolutionary cease-fire at Nature Communications, April 2018.

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dmrseq Powers-Up Whole-Genome Bisulfite Sequencing Analysis http://epigenie.com/dmrseq-powers-whole-genome-bisulfite-sequencing-analysis/ http://epigenie.com/dmrseq-powers-whole-genome-bisulfite-sequencing-analysis/#respond Mon, 16 Apr 2018 17:24:34 +0000 http://epigenie.com/?p=26974 In our modern world, power is everything. Whether it be political, social, or even statistical, humankind always thirsts for more. While political and social power may be a little beyond our scope, a new bioinformatic package has come forth to power up your ability to detect differentially methylated regions (DMRs) from whole-genome bisulfite sequencing (WGBS) data.

The identification of DMRs by WGBS is no easy task; the high cost of sequencing leads to low sample sizes with low coverage and thus the requirement for complex statistical inference. Further complications arise from the correlated nature of CpG sites, which makes controlling the false discovery rate (FDR) challenging. However, as the price of sequencing continues to plummet, WGBS has emerged as a truly genome-wide method that can be applied to complex experimental designs.

To tackle the challenges of identifying DMRs from WGBS data, the lab of Rafael Irizarry at Harvard University (USA) has brought forth dmrseq. dmrseq builds on the data structure of the popular bsseq (BSmooth) package, which was also developed in the Irizarry lab, but offers a very different approach.

The identification DMR employs two critical steps:

  1. DMR Detection: The differences in CpG methylation for the effect of interest are pooled and smoothed to give CpG sites with higher coverage a higher weight, and candidate DMRs are assembled
  2. Statistical Analysis: A region statistic for each DMR, which is comparable across the genome, is estimated via the application of a generalized least squares (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest. Then, permutation testing of a pooled null distribution enables the identification of significant DMRs
    • This approach accounts for both inter-individual and inter-CpG variability across the entire genome

Notably, by performing the statistical testing on DMRs and not CpGs, dmrseq offers accurate FDR control. This approach also allows the direct adjustment of covariates in the model, an ideal situation for covariates that are continuous or contain two or more groups. Covariates can also be incorporated by balancing the permutations, which is ideal for two group covariates such as sex. Finally, dmrseq also allows for multi-group comparisons and can identify DMRs with a sample size as low as two per group.

By comparing dmrseq to bsseq, DSS, and Metilene, and examining the differences in DMR identification in data from the human epigenome roadmap, mouse models, or simulations, the talented team demonstrated the powerful capabilities of dmrseq in identifying DMRs.

Behind the WGBS Power

First author Keegan Korthauer shares the motivation behind the creation of dmrseq, “We noticed that existing tools for DMR identification from WGBS data were actually focused on discovering DMCs (differentially methylated CpGs), and then grouping them together to form DMRs. While these types methods will provide a list of putative DMRs, they suffer from two main drawbacks: (1) There is no way to evaluate statistical significance of the list of DMRs. Even if we know about the statistical significance of each CpG, there is no formula that lets us compute the region-level significance from that information. (2) It is not clear how to rank the DMRs in terms of their signal. Most researchers have settled on using some sort of heuristic, such as the average methylation difference across all CpGs in the region, or the number of CpGs in the region, but these types of measures will be misleading when trying to compare areas of the genome that have different degrees of spatial correlation and variance of methylation levels. Thus, we set out to develop a method that would overcome these issues, and provide a list of DMRs that (1) has an accurate error rate, so that you can specify the proportion of false discoveries you are willing to consider, and (2) ranks regions according the strength of signal, adjusted for local properties of spatial correlation and variance.”

Korthauer continues with how dmrseq will enable new insight from WGBS, “dmrseq provides a powerful new way to identify DMRs involved in complex traits or diseases. Because dmrseq provides a way to control the proportion of false discoveries and ranks DMRs by strength of signal, it provides a more compelling list of regions for characterization or followup study. As we demonstrate, we see a large enrichment of (the expected) association with expression of nearby genes for the most significant DMRs by dmrseq as compared to the DMRs with the highest average methylation difference. Our hope is that our tool will enable researchers to gain better insight into the role of DNA methylation in various biological processes.”

Finally, Korthauer concludes with the outlook that, “Moving forward, a challenge in the identification of DMRs from WGBS is to perform inference simultaneously at multiple scales of resolution. Currently, DMR discovery is highly influenced by the level of smoothing, which you can think of as how far you ‘zoom out’ when looking at patterns in noisy methylation measurements across the genome. You can adjust this according to your prior knowledge, or the type of regions you are interested in (e.g. small local regions versus large-scale blocks), but the ability to detect the scale of resolution automatically will be much more informative. In addition, as the technology to perform WGBS in single cells is rapidly maturing, an additional challenge (and opportunity!) will be to accommodate cell-to-cell differences in methylation levels in DMR identification.”

Get your hands on the dmrseq package over at Bioconductor and check out the full article in Biostatistics, February 2018.

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If You Snooze, You Lose: DNA Methylation Loss at Late Replicating Regions Tracks Cellular Aging http://epigenie.com/snooze-lose-dna-methylation-loss-late-replicating-regions-tracks-cellular-aging/ http://epigenie.com/snooze-lose-dna-methylation-loss-late-replicating-regions-tracks-cellular-aging/#comments Sat, 14 Apr 2018 07:39:18 +0000 http://epigenie.com/?p=26968 “Early to bed and early to rise makes a man healthy, wealthy, and wise!” While many night owls happily ignore this sage advice and enjoy a few extra hours in bed in the mornings, a new study regarding DNA methylation dynamics in normal and cancer cells gives credence to the old axiom “If you snooze, you lose!” and may provide a means to track cellular aging!

More precisely, the bright eyed and bushy tailed researchers from the labs of Hui Shen, Peter W. Laird (Van Andel Research Institute), and Benjamin P. Berman (Cedars-Sinai Medical Center) have studied DNA methylation loss or hypomethylation at “lazier” regions of the genome, actually known as late-replicating regions. Previous studies have linked lamina-associated, late-replicating regions, otherwise known as partially methylated domains (PMDs), to various types of cancer and one study employed PMDs to trace the evolution of gene regulation in mammalian placentas. Fascinatingly, the author’s new findings establish that DNA methylation loss at late-replicating regions occurs progressively in most cells, beginning from even the earliest stages of development, and accurately tracks the number of cellular divisions made.

DNA Methylation Loss at Late Replicating Regions Tracks Cellular Aging

Here’s what the team discovered after applying advanced bioinformatics analysis to an extensive range of normal and cancerous mouse and human whole-genome bisulfite sequencing (WGBS) datasets, including tumor and adjacent normal data from eight common cancer types:

  • A WCGW motif (where W = A or T) without neighboring CpGs (solo) represented the most hypomethylation-prone motif within late-replicating sequences
  • A search for solo-WCGWs discovered previously undetected hypomethylation in the vast majority of healthy tissue types
    • DNA methylation loss starts from embryonic development and progressively increases with chronological age
  • solo-WCGW motif analysis in cancer cells demonstrated that higher mutation density and increased expression of proliferation-associated genes correlated to increased DNA methylation loss within late-replicating sequences
  • Therefore, the authors propose that the loss of DNA methylation at solo-WCGWs within these regions tracks the accumulation of cell divisions and can precisely establish cellular age, which may be different to the chronological age of the host

Conclusions: The View from the Early Risers

Let’s finish with the thoughts of the three study leaders, who surely get up very early in the morning:

“Our cellular clock starts ticking the moment our cells begin dividing,” Laird said. “This method allows us to track the history of these past divisions and measure age-related changes to the genetic code that may contribute to both normal aging and dysfunction.”

“What is striking about the results from our new method is that they push back the start of this process to the earliest stages of in utero development,” Berman said. “That was completely surprising, given the current assumption that the process begins relatively late on the path to cancer. This finding also suggests that it may play a functional role relatively early in the formation of tumors.”

“Tissues with higher turnover rates are typically more susceptible to cancer development simply because there are more opportunities for errors to accumulate and force the change from a normal cell to a malignant one,” Shen said. “What we’re seeing is a normal process — cellular aging — augmented and accelerated once a cell becomes cancerous. The cumulative effect is akin to a runaway freight train.”

Quit your snoozing and be the early bird who catches the scientific worm at Nature Genetics, April 2018.

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