Functional analysis and co-evolutionary model of chromatin and DNA methylation networks in embryonic stem cells
Enrique Carrillo de Santa Pau, Juliane Perner, David Juan, Simone Marsili, David Ochoa, Ho-Ryun Chung, Daniel Rico, Martin Vingron, Alfonso Valencia
doi: http://dx.doi.org/10.1101/008821
We have analyzed publicly available epigenomic data of mouse embryonic stem cells (ESCs) combining diverse next-generation sequencing (NGS) studies (139 experiments from 30 datasets with a total of 77 epigenomic features) into a homogeneous dataset comprising various cytosine modifications (5mC, 5hmC and 5fC), histone marks and Chromatin related Proteins (CrPs). We applied a set of newly developed statistical analysis methods with the goal of understanding the associations between chromatin states, detecting co-occurrence of DNA-protein binding and epigenetic modification events, as well as detecting coevolution of core CrPs. The resulting networks reveal the complex relations between cytosine modifications and protein complexes and their dependence on defined ESC chromatin contexts. A detailed analysis allows us to detect proteins associated to particular chromatin states whose functions are related to the different cytosine modifications, i.e. RYBP with 5fC and 5hmC, NIPBL with 5hmC and OGT with 5hmC. Moreover, in a co-evolutionary analysis suggesting a central role of the Cohesin complex in the evolution of the epigenomic network, as well as strong co-evolutionary links between proteins that co-locate in the ESC epigenome with DNA methylation (MBD2 and CBX3) and hydroxymethylation (TET1 and KDM2A). In summary, the new application of computational methodologies reveals the complex network of relations between cytosine modifications and epigenomic players that is essential in shaping the molecular state of ESCs.

Cross-population Meta-analysis of eQTLs: Fine Mapping and Functional Study

Xiaoquan Wen, Francesca Luca, Roger Pique-Regi
doi: http://dx.doi.org/10.1101/008797

Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at the molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistently presented across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL. ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 × 10-22).

Conservation of expression regulation throughout the animal kingdom

Michael Kuhn, Andreas Beyer
doi: http://dx.doi.org/10.1101/007252

Gene expression programs have been found to be highly conserved between closely related species, especially when comparing the same tissue types between species. Such analysis is, however, much more challenging over larger evolutionary distances when complementary tissues cannot readily be defined. Here, we present the first cross-species mapping of tissue-specific and developmental gene expression patterns across a wide range of animals, including many non-model species. Importantly, our approach does not require the definition of homologous tissues. In our survey of 32 datasets across 23 species, we detected conserved expression programs on all taxonomic levels, both within animals and between the animals and their closest unicellular relatives, the choanoflagellates. We found that the rate of change in tissue expression patterns is a property of gene families. Subsequently, we used the conservation of expression programs as a means to identify neofunctionalization of gene duplication products. We found 1206 duplication events where one of the two genes kept the expression program of the original gene, whereas the other copy adopted a novel expression program. We corroborated such potential neofunctionalizations using independent network information: the duplication product with the more conserved expression pattern shared more interaction partners with the non-duplicated reference gene than the more divergent duplication product. Our findings open new avenues of study for the comparison and transfer of knowledge between different species.