Maria Colomé-Tatché

Mapping the Epigenetic Basis of Complex Traits

Quantifying the impact of heritable epigenetic variation on complex traits is an emerging challenge in population genetics. Here, we analyze a population of isogenic Arabidopsis lines that segregate experimentally induced DNA methylation changes at hundreds of regions across the genome. We demonstrate that several of these differentially methylated regions (DMRs) act as bona fide epigenetic quantitative trait loci (QTLepi), accounting for 60 to 90% of the heritability for two complex traits, flowering time and primary root length. These QTLepi are reproducible and can be subjected to artificial selection. Many of the experimentally induced DMRs are also variable in natural populations of this species and may thus provide an epigenetic basis for Darwinian evolution independently of DNA sequence changes. Genetic mapping reveals epigenetic changes associated with flowering time and root length. [Also see Perspective by Schmitz] Plant Epigenetics Quantitative trait loci (QTLs) are genetic regions associated with phenotypic traits that help to determine the underlying genetics controlling the magnitude of a specific trait. Cortijo et al. (p. 1145, published online 6 February; see the Perspective by Schmitz) identified epigenetic QTLs associated with differences in methylation marks (epiQTLs) controlling flowering time and root length in the model plant Arabidopsis. These epiQTLs were mapped in genetically identical lines that differ only in their methylation marks. A small number of QTLs were able to explain up to 90% of the heritable variation in these traits. Thus, in plants, the heritability of some complex traits can be determined by epigenetic variation.

Genome-Wide Epigenetic Perturbation Jump-Starts Patterns of Heritable Variation Found in Nature

We extensively phenotyped 6000 Arabidopsis plants with experimentally perturbed DNA methylomes as well as a diverse panel of natural accessions in a common garden. We found that alterations in DNA methylation not only caused heritable phenotypic diversity but also produced heritability patterns closely resembling those of the natural accessions. Our findings indicate that epigenetically induced and naturally occurring variation in complex traits share part of their polygenic architecture and may offer complementary adaptation routes in ecological settings.

Features of the Arabidopsis recombination landscape resulting from the combined loss of sequence variation and DNA methylation

The rate of meiotic crossing over (CO) varies considerably along chromosomes, leading to marked distortions between physical and genetic distances. The causes underlying this variation are being unraveled, and DNA sequence and chromatin states have emerged as key factors. However, the extent to which the suppression of COs within the repeat-rich pericentromeric regions of plant and mammalian chromosomes results from their high level of DNA polymorphisms and from their heterochromatic state, notably their dense DNA methylation, remains unknown. Here, we test the combined effect of removing sequence polymorphisms and repeat-associated DNA methylation on the meiotic recombination landscape of an Arabidopsis mapping population. To do so, we use genome-wide DNA methylation data from a large panel of isogenic epigenetic recombinant inbred lines (epiRILs) to derive a recombination map based on 126 meiotically stable, differentially methylated regions covering 81.9% of the genome. We demonstrate that the suppression of COs within pericentromeric regions of chromosomes persists in this experimental setting. Moreover, suppression is reinforced within 3-Mb regions flanking pericentromeric boundaries, and this effect appears to be compensated by increased recombination activity in chromosome arms. A direct comparison with 17 classical Arabidopsis crosses shows that these recombination changes place the epiRILs at the boundary of the range of natural variation but are not severe enough to transgress that boundary significantly. This level of robustness is remarkable, considering that this population represents an extreme with key recombination barriers having been forced to a minimum.

Rate, spectrum, and evolutionary dynamics of spontaneous epimutations

Significance Changes in the methylation status of cytosine nucleotides are a source of heritable epigenetic and phenotypic diversity in plants. Here we derive robust estimates of the rate at which cytosine methylation is spontaneously gained (forward epimutation) or lost (backward epimutation) in the genome of the model plant Arabidopsis thaliana. We show that the forward–backward dynamics of selectively neutral epimutations have a major impact on methylome evolution and shape genome-wide patterns of methylation diversity among natural populations in this species. The epimutation rates presented here can serve as reference values in future empirical and theoretical population epigenetic studies in plants. Stochastic changes in cytosine methylation are a source of heritable epigenetic and phenotypic diversity in plants. Using the model plant Arabidopsis thaliana, we derive robust estimates of the rate at which methylation is spontaneously gained (forward epimutation) or lost (backward epimutation) at individual cytosines and construct a comprehensive picture of the epimutation landscape in this species. We demonstrate that the dynamic interplay between forward and backward epimutations is modulated by genomic context and show that subtle contextual differences have profoundly shaped patterns of methylation diversity in A. thaliana natural populations over evolutionary timescales. Theoretical arguments indicate that the epimutation rates reported here are high enough to rapidly uncouple genetic from epigenetic variation, but low enough for new epialleles to sustain long-term selection responses. Our results provide new insights into methylome evolution and its population-level consequences.

Quantitative Epigenetics Through Epigenomic Perturbation of Isogenic Lines

Interindividual differences in chromatin states at a locus (epialleles) can result in gene expression changes that are sometimes transmitted across generations. In this way, they can contribute to heritable phenotypic variation in natural and experimental populations independent of DNA sequence. Recent molecular evidence shows that epialleles often display high levels of transgenerational instability. This property gives rise to a dynamic dimension in phenotypic inheritance. To be able to incorporate these non-Mendelian features into quantitative genetic models, it is necessary to study the induction and the transgenerational behavior of epialleles in controlled settings. Here we outline a general experimental approach for achieving this using crosses of epigenomically perturbed isogenic lines in mammalian and plant species. We develop a theoretical description of such crosses and model the relationship between epiallelic instability, recombination, parent-of-origin effects, as well as transgressive segregation and their joint impact on phenotypic variation across generations. In the limiting case of fully stable epialleles our approach reduces to the classical theory of experimental line crosses and thus illustrates a fundamental continuity between genetic and epigenetic inheritance. We consider data from a panel of Arabidopsis epigenetic recombinant inbred lines and explore estimates of the number of quantitative trait loci for plant height that resulted from a manipulation of DNA methylation levels in one of the two isogenic founder strains.

Genetic sources of population epigenomic variation

The field of epigenomics has rapidly progressed from the study of individual reference epigenomes to surveying epigenomic variation in populations. Recent studies in a number of species, from yeast to humans, have begun to dissect the cis- and trans-regulatory genetic mechanisms that shape patterns of population epigenomic variation at the level of single epigenetic marks, as well as at the level of integrated chromatin state maps. We show that this information is paving the way towards a more complete understanding of the heritable basis underlying population epigenomic variation. We also highlight important conceptual challenges when interpreting results from these genetic studies, particularly in plants, in which epigenomic variation can be determined both by genetic and epigenetic inheritance.

Single-cell whole genome sequencing reveals no evidence for common aneuploidy in normal and Alzheimer's disease neurons

BackgroundAlzheimer’s disease (AD) is a neurodegenerative disease of the brain and the most common form of dementia in the elderly. Aneuploidy, a state in which cells have an abnormal number of chromosomes, has been proposed to play a role in neurodegeneration in AD patients. Several studies using fluorescence in situ hybridization have shown that the brains of AD patients contain an increased number of aneuploid cells. However, because the reported rate of aneuploidy in neurons ranges widely, a more sensitive method is needed to establish a possible role of aneuploidy in AD pathology.ResultsIn the current study, we used a novel single-cell whole genome sequencing (scWGS) approach to assess aneuploidy in isolated neurons from the frontal cortex of normal control individuals (n = 6) and patients with AD (n = 10). The sensitivity and specificity of our method was shown by the presence of three copies of chromosome 21 in all analyzed neuronal nuclei of a Down’s syndrome sample (n = 36). Very low levels of aneuploidy were found in the brains from control individuals (n = 589) and AD patients (n = 893). In contrast to other studies, we observe no selective gain of chromosomes 17 or 21 in neurons of AD patients.ConclusionscWGS showed no evidence for common aneuploidy in normal and AD neurons. Therefore, our results do not support an important role for aneuploidy in neuronal cells in the pathogenesis of AD. This will need to be confirmed by future studies in larger cohorts.

Ecological plant epigenetics: Evidence from model and non-model species, and the way forward

Growing evidence shows that epigenetic mechanisms contribute to complex traits, with implications across many fields of biology. In plant ecology, recent studies have attempted to merge ecological experiments with epigenetic analyses to elucidate the contribution of epigenetics to plant phenotypes, stress responses, adaptation to habitat, and range distributions. While there has been some progress in revealing the role of epigenetics in ecological processes, studies with non-model species have so far been limited to describing broad patterns based on anonymous markers of DNA methylation. In contrast, studies with model species have benefited from powerful genomic resources, which contribute to a more mechanistic understanding but have limited ecological realism. Understanding the significance of epigenetics for plant ecology requires increased transfer of knowledge and methods from model species research to genomes of evolutionarily divergent species, and examination of responses to complex natural environments at a more mechanistic level. This requires transforming genomics tools specifically for studying non-model species, which is challenging given the large and often polyploid genomes of plants. Collaboration among molecular geneticists, ecologists and bioinformaticians promises to enhance our understanding of the mutual links between genome function and ecological processes.

Single-cell sequencing reveals karyotype heterogeneity in murine and human malignancies

BackgroundChromosome instability leads to aneuploidy, a state in which cells have abnormal numbers of chromosomes, and is found in two out of three cancers. In a chromosomal instable p53 deficient mouse model with accelerated lymphomagenesis, we previously observed whole chromosome copy number changes affecting all lymphoma cells. This suggests that chromosome instability is somehow suppressed in the aneuploid lymphomas or that selection for frequently lost/gained chromosomes out-competes the CIN-imposed mis-segregation.ResultsTo distinguish between these explanations and to examine karyotype dynamics in chromosome instable lymphoma, we use a newly developed single-cell whole genome sequencing (scWGS) platform that provides a complete and unbiased overview of copy number variations (CNV) in individual cells. To analyse these scWGS data, we develop AneuFinder, which allows annotation of copy number changes in a fully automated fashion and quantification of CNV heterogeneity between cells. Single-cell sequencing and AneuFinder analysis reveals high levels of copy number heterogeneity in chromosome instability-driven murine T-cell lymphoma samples, indicating ongoing chromosome instability. Application of this technology to human B cell leukaemias reveals different levels of karyotype heterogeneity in these cancers.ConclusionOur data show that even though aneuploid tumours select for particular and recurring chromosome combinations, single-cell analysis using AneuFinder reveals copy number heterogeneity. This suggests ongoing chromosome instability that other platforms fail to detect. As chromosome instability might drive tumour evolution, karyotype analysis using single-cell sequencing technology could become an essential tool for cancer treatment stratification.

Natural variation of histone modification and its impact on gene expression in the rat genome

Histone modifications are epigenetic marks that play fundamental roles in many biological processes including the control of chromatin-mediated regulation of gene expression. Little is known about interindividual variability of histone modification levels across the genome and to what extent they are influenced by genetic variation. We annotated the rat genome with histone modification maps, identified differences in histone trimethyl-lysine levels among strains, and described their underlying genetic basis at the genome-wide scale using ChIP-seq in heart and liver tissues in a panel of rat recombinant inbred and their progenitor strains. We identified extensive variation of histone methylation levels among individuals and mapped hundreds of underlying cis- and trans-acting loci throughout the genome that regulate histone methylation levels in an allele-specific manner. Interestingly, most histone methylation level variation was trans-linked and the most prominent QTL identified influenced H3K4me3 levels at 899 putative promoters throughout the genome in the heart. Cis- acting variation was enriched in binding sites of distinct transcription factors in heart and liver. The integrated analysis of DNA variation together with histone methylation and gene expression levels showed that histoneQTLs are an important predictor of gene expression and that a joint analysis significantly enhanced the prediction of gene expression traits (eQTLs). Our data suggest that genetic variation has a widespread impact on histone trimethylation marks that may help to uncover novel genotype-phenotype relationships.