Research
Research Focus
Our group studies the evolution of primates. We are especially interested in the molecular forces that shape phenotypic differences between primate species. What makes us human? Why does a chimpanzee look like a chimpanzee? While the genomic information of several primate species is available, we are still far from translating genomic differences into specific phenotypic effects.
Our main focus is on the impact of transcription factors (TFs) on differences in transcriptomes, gene regulatory networks, and ultimately the phenotype. TFs are proteins that form gene regulatory networks to regulate the expression of all genes. TFs typically bind to specific DNA sequence motives to control the expression of a few to many other genes. Therefore, evolutionary changes in TFs can potentially have large impacts on the phenotype of a species. Indeed, we demonstrated that some TF genes show significantly more sequence and expression differences between humans and chimpanzees than other types of genes. Intriguingly, some of these fast fast evolving TFs seem to play a role in brain and cognitive functions.
We are using experimental as well as computational approaches to investigate the evolution of primate TFs. Our major goals are to:
1. Identify all TFs of each primate species to pinpoint which TFs were born or lost in which lineage (The Primate TFome).
2. Functionally characterize species-specific TFs and TFs that changed species-specifically (Comparative Functional Characterization of TFs).
3. Understand how evolutionary changes in TFs affect gene regulatory network differences between primate species (Evolution of TF Networks).
In addition, we are also interested in other factors that influence transcriptomic differences, such as the evolution of non-coding RNAs and the epigenome (Long Non-Coding RNAs in Primate Brain Evolution). We furthermore investigate within-species differences of TFs, such as copy number variations, sequence and expression differences. In two further studies we investigate the impact of TFs and transcriptome differences on speciation in mammals and reptiles (Chromosomal Speciation).
To learn more about our own species we also have to understand the biology of our closest living relatives. Unfortunately, this opportunity might be lost in the near future. With the expansion of the human species in the last ~10.000 years came along a dramatic reduction in the population size of non-human primates. Presently, all great apes and many primates are endangered (IUCN 2008 Red List of Threatened Species). Main causes are the destruction of their remaining habitats in Central Africa and Asia as well as poaching, and the threat of introduced viruses in the primate communities.
Our group is supported by the Volkswagen Foundation.
Projects
The content of transcription factors (TFs) in the human genome (~1500 TFs) was just recently determined and is still unknown in most other sequenced genomes. The most significant problem for determining the exact TF content in the other genomes is the insufficient quality of their draft genomes, which makes it difficult to identify TFs in the complicated genome areas. Furthermore, the lack of transcript information (mRNA, cDNA, or EST sequences) makes it difficult to determine the sequence of the transcribed genes, because the prediction of promoters, open reading frames, and splice sites has to be done purely based on genomic features and conservation to other species. We take advantage of improved genomic information and increasing amounts of transcript data provided by RNA-Seq to computationally identify all TFs in primate genomes and to manually curate gene models for TFs in humans, chimpanzees, orangutan, rhesus macaque, and marmoset. We are using our high-quality TF gene models to reveal lineage- and species-specific TFs, TFs that have lineage- or species-specific changes in functional domains, and TFs under positive selection.
Comparative Functional Characterization of Transcription Factors
Only a small proportion of TFs has been functionally characterized. Very little is known about many gene families, and this situation is especially dramatic for the biggest TF family in mammalian genomes: the KRAB-ZNFs. The importance of TFs for phenotypic differences and speciation has been established for various examples (e.g. PRDM9, FOXP2, EGR1, BMP4). We are focussing on human-specific TFs, TFs with human-specific domain changes, and TFs that are connected in gene regulatory networks in a human-specific way to determine experimentally their evolutionary impact. We perform for instance ChIP-Seq experiments in human and chimpanzee cell lines to identify the binding sites of the TFs in both species. Furthermore, we manipulate expression levels of the TFs in cell lines of both species (knock-down and overexpression) followed by RNA-Seq to determine downstream targets. These experiments will not only give us insight into the function of the selected TFs, but more importantly, insight into their functional changes during evolution.
Evolution of Transcription Factor Networks
TFs regulate their target genes in a concerted, combinatorial fashion, thus forming often large and complex gene regulatory networks. Little is known about the evolution of such networks, about the amount of noise or redundancy in such networks, and the importance of gain or loss of nodes (genes) or links (interaction). Based on transcriptome information, we have previously identified a network of TFs that is active in the prefrontal cortex and is characterized by significant link changes between humans and chimpanzees. It appears that this network was involved in shaping some phenotypic differences, such as the larger human brain and its higher energy consumption. We are now investigating this TF network in other primates to reveal its evolutionary history. Furthermore we are interested in network differences between human populations.
Long Non-Coding RNAs in Primate Brain Evolution
Joint project with Professor Peter Stadler (Bioinformatics group Leipzig).
Long non-coding RNAs (lncRNAs) are emerging as key players in the nervous system. Many of the about 15.000 human lncRNAs are expressed in the brain and multiple lines of evidence have linked them to important brain functions, such as neurogenesis and behavior, or have associated them with neurodegenerative and psychiatric diseases. Although several databases for lncRNAs exist, there is still a large gap in the structural and functional annotation of lncRNAs hindering a full understanding of their role in the nervous system. Many characteristics of the brain are human specific. Genes that evolve quickly, as lncRNAs do, are therefore the best candidates to be primarily responsible for the evolution of these innovations. Since biological function has to be studied in the light of evolution, we aim here at establishing a full catalog of human lncRNAs, including an annotation of their sequence, structure, expression, and evolutionary changes by collating and coherently re-analyzing the wealth of already available high throughout data. We will experimentally determine target genes for one selected lncRNA and for the other lncRNA genes provide insights into their function and involvement in gene regulatory networks using computational methods. These results, together with the custom brain-lncRNA chip we plan to develop, will set the stage for thorough functional characterization of lncRNAs in the brain during the second funding period.
Monoallelic expression as a potential trigger of cognitive diseases
Random monoallelic expression (RMAE) is a mechanism, in which only one allele of a gene is expressed. Since the allele is randomly chosen, this gene expression mode can create variability between cells of the same cell type and might be one mechanism to render some neurons more sensitive than others to developing pathologies. RMAE has been shown to be involved in cognitive diseases, such as schizophrenia and autism, and in neurodevelopmental disorders. Alzheimer (AD) -associated genes are significantly enriched among RMAE genes, suggesting a link between AD and RMAE. Moreover, the AD-characteristic amyloid precursor protein (APP) is expressed monoallelically, potentially leading to different amounts of APP in different cells. We are using single neuron sequencing to test the hypothesis, that patterns of RMAE are altered in neurons of individuals with AD. Using state-of-the-art comparative transcriptome and co-expression network analyses we aim to uncover functional consequences of changes in RMAE that might be related to AD.
The mtDNA and the Y chromosome are commonly used uniparental markers in population genetics that provide information on the history and relationships of populations and individuals. However, genetic profiles of a population inferred from mtDNA vs. the MSY often differ from each other, and from the genetic profile inferred from autosomal markers – which could be driven by the differences in the maternal and paternal histories of human populations. Recently, many populations have been described using both uniparental and autosomal markers, however, we still know very little about associations of uniparental (mtDNA and Y chromosome) haplogroups with autosomal ancestry components. Synergistically using mtDNA and Y chromosome haplogroup compositions together with autosomal ancestry components we are trying to define “ancestry packages”, i.e. associated combinations of mtDNA, Y chromosome haplogroups, and autosomal ancestry components, which are indicative of ancestral genetic compositions. The ancestry packages approach can be used to objectively classify the likely geographic origin of haplogroups (and other markers for which population estimates are available) in accordance with autosomal ancestry components and can be further used to infer the potential direction and composition of sex-biased gene flow between different ancestral populations.
Genomic distribution of sequence and gene expression differences between mammalian species: the importance of chromosomal rearrangements in speciation
Joint project with Dr. Rui Faria (Research Center in Biodiversity and Genetic Resources, Porto, Portugal).
Alterations in the spatial organization of the genome (chromosomal rearrangements (CRs)) can cause divergence in coding sequences, in sequences of regulatory regions, and in gene expression. Our working hypothesis is that these types of changes are correlated with hybrid sterility and/or inviability, and thus can lead to speciation. We are testing this hypothesis by evaluating the relative contribution of CRs and of changes in the composition of the neighborhood of genes on gene expression divergence between species. We further analyze if sequence and expression divergence are correlated. In addition, we aim to investigate how gene regulatory and co-expression networks that contain genes with changed genomic location differ between species. By exploring these networks and the functions of genes that are located within CRs and display high expression divergence we aim to gain insight into why hybrids are sterile or inviable.
Accelerated Evolution in Chromosomal Rearrangements and Speciation in Lacertid Lizards
Joint project with Prof. Martin Schlegel, Prof. Peter Stadler, Dr. Klaus Henle, and Dr. Rui Faria within the German Centre for Integrative Biodiversity Research (iDiv).
During the process of speciation, individuals of two populations acquire genetic differences leading to reproductive isolation. According to Suppressed Recombination Models (SRMs) of chromosomal speciation, genetic divergence can quickly accumulate within regions of low recombination, such as in chromosomal rearrangements (CRs). We are testing the hypothesis that CRs are associated with accelerated evolution driving speciation by studying two species of lizards (Lacerta viridis and L. bilineata) which recently separated during Pleistocene. To this end, we are sequencing, assembling, and comparing their genomes, to search for accumulated divergence near breakpoints and within rearranged regions. We are also sequencing the transcriptomes of four individuals of each species as well as four hybrids for gene annotation and identification of differential gene expression patterns. We are further developing a new gene assembly method to detect CRs. In the spirit of iDiv we want to contribute to a better understanding of mechanisms of speciation and of how biodiversity emerges.
Impact of radiation on species fitness
Higher organism rely on their cognitive abilities to compete for resources such as food, territories and mates: brain function is thus directly linked with fitness. There seems to be a link between brain size and cognitive performance at least in humans, since microcephaly usually goes along with cognitive disabilities. Development of the brain is sensitive to the environment, with stress during early life negatively affecting brain development, functions and cognition. Here, together with Dr. Zbyszek Boratynski, we aim to decipher the transcriptome and co-expression network signatures that determine brain size using two species of wild rodents (Apodemus and Myodes) from Chornobyl (Ukraine). We sequence the transcriptomes of the frontal cortex, hippocampus, amygdala, and motor cortex from individuals inhabiting areas with contrasting levels of soil radionuclide contamination to determine differences in gene expression and co-expression networks. From the very same individuals we also obtained measurements on their performance in behavioral tests, their basal metabolic rate, and brain mass to link the transcriptome patterns to energetic costs, brain size and cognitive performance.
Genetics of mating behavior and reproductive success
Social behaviors involve the interactions of one individual with another and are related to mating and reproduction success, hence fitness. The genetic basis of complex phenotypes typically involves a large number of genes. For example, much of the variation in social behaviour observed among vertebrates can at least in part be explained, by variation in gene expression networks located in the brain. In the project with Dr. Clemens Küpper, we use a highly amenable vertebrate study system, the Ruff Philomachus pugnax, to study how an autosomal inversion modifies gene expression and regulation and ultimately leads to discrete variation in male aggression and courtship. Our project involves the assembly and annotation of the ruff genome, comparative transcriptomics in a broad range of brain regions and other tissues in adult and young individuals.
Repeated evolution and loss of pollen-collecting structures in bees
The loss of phenotypes represents a type of evolutionary innovation and is a widespread phenomenon. Like phenotypic gain, it can be adaptive and lead to new life histories. However, compared to phenotype gain, it is less well studied. A particularly interesting case for evolutionary studies is the repeated loss of the same phenotype in independent lineages, because this allows for investigating the repeatability, and to some extent predictability, of evolution. Here we study the genomic basis of repeated phenotypic loss using pollen-collecting structures as example. These structures have evolved in several independent bee lineages and facilitated the evolutionary success of these lineages as pollinators. Interestingly, they have been lost in more than a dozen independent lineages of kleptoparasitic bees, along with certain behaviors and pilosity. In our project with Dr. Eckart Stolle, we produce and analyze more than 100 bee genomes to reveal the emergence of that phenotypic loss within a phylogenetic framework. As pollen collecting structures seems to be gained and lost dynamically during evolution, we hypothesize that gene regulatory changes play an important role in achieving such phenotypic plasticity. Hence, we also produce transcriptomes and ATAC-Seq data from six species, precisely three pairs of host and kleptoparasitic species having gained or lost the structures. In addition, we will investigate shifts in selective pressures acting on coding and non-coding sequences to understand how they might have conveyed the repeated loss of pollen collecting structures.
Comparative skylight navigation
The sun and the sky are amongst the most ancient visual cues for terrestrial navigation. Navigation skills are essential for successful hunting, foraging, or dispersal of most free-living species. Insects use different visual stimuli, like celestial bodies and skylight polarization. While systematic morphological characterization has identified retinal detectors for polarized skylight in virtually all insects analyzed, it remains unknown whether specification of these structures and their underlying neural circuitry are in fact evolutionarily conserved. Moreover, it is unknown how they are adapted to the diverse ecological niches of different insect species. In this proposal, together with Prof. Mathias Wernet, we are investigating how variations in the transcription factor networks shape the skylight detector system in adaptation to species-specific demands. We are using a combination of different bioinformatics methods to compare regulatory sequences, transcription factor binding sites, transcription factor networks, and gene expression profiles across insects, including flies, butterflies, mosquitos, bees and others to reveal evolutionarily conserved mechanisms as well as species-specific adaptations behind the formation of neural circuits for insect skylight navigation.
Kin-driven behaviour influences social relationships and can have crucial importance for health and fitness of individuals. Notably, the amount of the genome shared by relatives varies considerably due to stochastic processes during meiosis, resulting in a gradient of IBD (identity-by-descent) values. In this project with Anja Widdig, we will take advantage of a population of free-ranging rhesus macaques (Macaca mulatta) at Cayo Santiago (Puerto Rico), for which demographic, reproductive, behavioural, and other phenotypic data have been collected over decades. We will sequence the whole genomes of ~1000 of those rhesus macaque individuals to determine their IBD to assess the impact of the gradient in IBD on social preferences for and against kin. With this project we aim to contribute to understanding how realized relatedness shapes sociality and biodiversity.
We created interactive network representations to explore the evolution of transcription factor networks in different brain regions as well as kidney and muscle in humans, chimpanzees, and rhesus macaques. To explore these networks, download the NetVisualizations file, unzip it, and open the html files.
We constructed a transcription factor Consensus network of the human frontal lobe. To explore this network, download the Consensus file, change the ending to .cys, and open in in Cytoscape version 3.0 or higher.