DNA methylome-wide alterations associated with estrogen receptor-dependent effects of bisphenols in breast cancer.

BACKGROUND: Bisphenol A (BPA), an estrogen-like endocrine disruptor used in plastics, has been associated with development and promotion of breast cancer, so plastic manufacturers shifted towards less-studied analogs, BPF and BPS. Studying the associated DNA methylome-wide mechanisms of these derivatives is timely, particularly in comparison with BPA. METHODS: We assessed proliferation, cell cycle, and migration of breast cancer cells (estrogen receptor (ER)-positive: MCF-7 and ER-negative: MDA-MB-231) treated with BPF and BPS ± estrogen receptor inhibitor (ERI) in comparison to BPA ± ERI. RNA expression and activity of DNA (de)methylation enzymes and LINE-1 methylation were quantified. DNA methylome-wide analysis was evaluated in bisphenol-exposed cells and compared to clinical breast cancer data. RESULTS: The three bisphenols caused ER-dependent increased proliferation and migration of MCF-7 but not MDA-MB-231 cells, with BPS being 10 times less potent than BPA and BPF. Although they have similar chemical structures, the three bisphenols induced differential DNA methylation alterations at several genomic clusters of or single CpG sites, with the majority of these being ER-dependent. At equipotent doses, BPA had the strongest effect on the methylome, followed by BPS then BPF. No pathways were enriched for BPF while BPA- and BPS-induced methylome alterations were enriched in focal adhesion, cGMP-PKG, and cancer pathways, which were also dysregulated in methylome-wide alterations comparing ER-positive breast cancer samples to adjacent normal tissues. CONCLUSIONS: The three bisphenols have important epigenetic effects in breast cell lines, with those of BPA and BPS overlapping with cancer-related pathways in clinical breast cancer models. Hence, further investigation of their safety is warranted.

DNA methylation signal has a major role in the response of human breast cancer cells to the microenvironment.

Breast cancer-associated fibroblasts (CAFs) have a crucial role in tumor initiation, metastasis and therapeutic resistance by secreting various growth factors, cytokines, protease and extracellular matrix components. Soluble factors secreted by CAFs are involved in many pathways including inflammation, metabolism, proliferation and epigenetic modulation, suggesting that CAF-dependent reprograming of cancer cells affects a large set of genes. This paracrine signaling has an important role in tumor progression, thus deciphering some of these processes could lead to relevant discoveries with subsequent clinical implications. Here, we investigated the mechanisms underlying the changes in gene expression patterns associated with the cross-talk between breast cancer cells and the stroma. From RNAseq data obtained from breast cancer cell lines grown in presence of CAF-secreted factors, we identified 372 upregulated genes, exhibiting an expression level positively correlated with the stromal content of breast cancer specimens. Furthermore, we observed that gene expression changes were not mediated through significant DNA methylation changes. Nevertheless, CAF-secreted factors but also stromal content of the tumors remarkably activated specific genes characterized by a DNA methylation pattern: hypermethylation at transcription start site and shore regions. Experimental approaches (inhibition of DNA methylation, knockdown of methyl-CpG-binding domain protein 2 and chromatin immunoprecipitation assays) indicated that this set of genes was epigenetically controlled. These data elucidate the importance of epigenetics marks in the cancer cell reprogramming induced by stromal cell and indicated that the interpreters of the DNA methylation signal have a major role in the response of the cancer cells to the microenvironment.

Comparative population genomics in animals uncovers the determinants of genetic diversity.

Genetic diversity is the amount of variation observed between DNA sequences from distinct individuals of a given species. This pivotal concept of population genetics has implications for species health, domestication, management and conservation. Levels of genetic diversity seem to vary greatly in natural populations and species, but the determinants of this variation, and particularly the relative influences of species biology and ecology versus population history, are still largely mysterious. Here we show that the diversity of a species is predictable, and is determined in the first place by its ecological strategy. We investigated the genome-wide diversity of 76 non-model animal species by sequencing the transcriptome of two to ten individuals in each species. The distribution of genetic diversity between species revealed no detectable influence of geographic range or invasive status but was accurately predicted by key species traits related to parental investment: long-lived or low-fecundity species with brooding ability were genetically less diverse than short-lived or highly fecund ones. Our analysis demonstrates the influence of long-term life-history strategies on species response to short-term environmental perturbations, a result with immediate implications for conservation policies.

Population genomics of eusocial insects: the costs of a vertebrate-like effective population size.

The evolution of reproductive division of labour and social life in social insects has lead to the emergence of several life-history traits and adaptations typical of larger organisms: social insect colonies can reach masses of several kilograms, they start reproducing only when they are several years old, and can live for decades. These features and the monopolization of reproduction by only one or few individuals in a colony should affect molecular evolution by reducing the effective population size. We tested this prediction by analysing genome-wide patterns of coding sequence polymorphism and divergence in eusocial vs. noneusocial insects based on newly generated RNA-seq data. We report very low amounts of genetic polymorphism and an elevated ratio of nonsynonymous to synonymous changes ­ a marker of the effective population size ­ in four distinct species of eusocial insects, which were more similar to vertebrates than to solitary insects regarding molecular evolutionary processes. Moreover, the ratio of nonsynonymous to synonymous substitutions was positively correlated with the level of social complexity across ant species. These results are fully consistent with the hypothesis of a reduced effective population size and an increased genetic load in eusocial insects, indicating that the evolution of social life has important consequences at both the genomic and population levels.

Reference-free transcriptome assembly in non-model animals from next-generation sequencing data.

Next-generation sequencing (NGS) technologies offer the opportunity for population genomic study of non-model organisms sampled in the wild. The transcriptome is a convenient and popular target for such purposes. However, designing genetic markers from NGS transcriptome data requires assembling gene-coding sequences out of short reads. This is a complex task owing to gene duplications, genetic polymorphism, alternative splicing and transcription noise. Typical assembling programmes return thousands of predicted contigs, whose connection to the species true gene content is unclear, and from which SNP definition is uneasy. Here, the transcriptomes of five diverse non-model animal species (hare, turtle, ant, oyster and tunicate) were assembled from newly generated 454 and Illumina sequence reads. In two species for which a reference genome is available, a new procedure was introduced to annotate each predicted contig as either a full-length cDNA, fragment, chimera, allele, paralogue, genomic sequence or other, based on the number of, and overlap between, blast hits to the appropriate reference. Analyses showed that (i) the highest quality assemblies are obtained when 454 and Illumina data are combined, (ii) typical de novo assemblies include a majority of irrelevant cDNA predictions and (iii) assemblies can be appropriately cleaned by filtering contigs based on length and coverage. We conclude that robust, reference-free assembly of thousands of genes from transcriptomic NGS data is possible, opening promising perspectives for transcriptome-based population genomics in animals. A Galaxy pipeline implementing our best-performing assembling strategy is provided.