Because evolutionary changes in gene regulatory factors (GRFs), such as transcription factors, can have a big impact on changing the phenotype between species, we set out to test all human GRFs proteins for positive selection within primates. Using information from 27 publicly available primate genomes we especially focused on the human lineage. From more than 3,000 human GRFs, we revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.
Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution
Vladimir M. Jovanovic, Melanie Sarfert, Carlos S. Reyna-Blanco, Henrike Indrischek, Dulce I. Valdivia, Ekaterina Shelest, and Katja Nowick
In an international collaboration we investigated the evolution of tissue-specific genes in the Lacerta viridis complex (European green lizard). We had sequenced and analyzed the genomes of three species/lineages and detected gene flow between the Adriatic lineage and L. viridis, suggesting that the evolutionary history of the L. viridis complex is likely shaped by gene flow. Genes highly expressed in the ovaries experienced accelerated evolution presumably contributing to establishing reproductive isolation in the Lacerta viridis complex. In addition, we built co-expression networks and found that genes that are strongly co-expressed in the brain also show accelerated evolution, potentially pointing to the evolution of behavioral differences between the species. Such accelerated evolution of tissue-specific genes might allow for speciation amidst gene flow in European green lizards.
Accelerated evolution of tissue-specific genes mediates divergence amidst gene flow in European green lizards
We have been featured in the German newspaper Tagesspiegel.
Here is the English translation of that article.
Our paper about CoDiNA, a method for comparing coexpression networks, has been accepted for publication by PLoS One. To our knowledge, it is the first method that allows for a comparison of transcriptome-wide networks and of as many networks as you wish. It can be applied to a diverse range of research questions, for instance to comparing coexpression networks, gene regulatory networks, abundance networks, and other types of networks. Networks can be compared between cell-types, tissues, species, or time-points, among others. Just let your imagination play. You will get as output information on which links are conserved across the networks you compare and which links have changed, either by being present in only a subset of networks or by having changed in their sign in some networks. Further, nodes are classified as conserved, specific or diverged between networks.
The development of CoDiNA was a big collaborative effort with most contributions from Eivind Almaas and Deisy Gysi. CoDiNA is implemented as an R package.
Gysi, D.M., Fragoso, T. de M., Zebardast, F., Bertoli, W., Busskamp, V., Almaas, E., and Nowick, K. (2020) CoDiNA: an R Package for Co-expression Differential Network Analysis in n Dimensions, PLoS One, 2020
Yao-Chung is finally present in Berlin. Welcome Yao-Chung!
For a few months now, we have a couple of new group members:
- Postdoc: Vladimir Bajić
- PhD students: Tima Zebardast and Yao-Chung Chen
Due to the COVID-19 situation, they haven’t physically joined us yet in Berlin. But we hope that they will soon be allowed to travel and start their projects here.
In the meantime, we are having online meetings and coffee breaks:
We have published an invited headline review in the Journal of the Royal Society Interface on the Construction, comparison and evolution of networks in life sciences and other disciplines. Our paper describes how biological networks change over time – in relatively short scales like during signal transduction and in relatively long scales like during development and evolution. We give a comprehensive overview about existing methods for analyzing such network changes. Moreover, we take a survey across non-biological sciences to explore how they investigate network changes. Our survey includes also some entertaining examples on the evolution of cooking recipes and the Marvel Universe.
We are offering a fully funded PhD position in our lab to work on the analysis of gene expression differences between brain of Alzheimer’s patients and controls. The focus will be on mono-allelically expressed genes to test the hypothesis that they are involved in establishing cellular diversity and selective vulnerability.
See the complete advertisement here: PhD_AlzheimerExpressionSignatures
We have acquired funding for a PhD position within a project that investigates a relationship between brain size and cognitive abilities in rodents from Chernobyl. We are interested in deciphering molecular signatures that determine differences in brain size and behavior.
See the complete advertisement here: PhD_BrainEvolution
We currently have an opening for a postdoc, with some flexibility about the actual research topic. The postdoc is expected to propose and develop a research project that fits to the general interests of the group. Requirements for the position are a Dr. rer. nat. or PhD in Biology or Bioinformatics or another relevant field. The ideal candidate would have a strong interest in human evolution and expertise within multiple of the following areas: conducting research with induced pluripotent stem cells, differentiation into neuronal cells, CRISPR/Cas9, functional investigation of transcription factors and non-coding RNAs, ChIP-Seq, ChIRP-Seq, RNA-Seq, gene regulatory networks, computational analysis of –omics data, R, Python, network analysis.
See the complete advertisement here: Postdoc_HumanEvolution.