Evolution of Molecular Circuitries
A comparative approach to human molecular biology
“Progress in science depends on new techniques, new discoveries and new ideas, probably in that order.” (Sidney Brenner)
We develop genomic and cellular tools to uncover biology contained in molecular variation among primates. We work closely with the computational lab of Ines Hellmann.
Research
Cross-species comparisons are essential for understanding human biology, disease, and evolution. They help identify functional elements in the genome, assess the relevance and limitations of model organisms, and reveal changes that emerged during the evolution of a new type of animal—us. Such comparative approaches provide a unique molecular perspective on who we are.
We investigate how human-specific changes in the transcription factor FOXP2 contributed to the evolution of speech and language using mouse models, and we study how and why molecular phenotypes, such as gene expression, change—or remain conserved—during primate development. Addressing these questions requires efficient and scalable measurements of molecular phenotypes, and we therefore devote substantial effort to applying and optimizing bulk and single-cell RNA-seq approaches. It also requires experimental access to relevant cellular systems. Because induced pluripotent stem cells (iPSCs) and their derivatives have transformed such access in humans, we are working to extend this opportunity across species by generating iPSCs from a broad range of primates.
Research Topics
To understand the molecular basis of evolutionary changes, experimentally accessible cells from different species are crucial. Induced pluripotent stem cells (iPSCs) and their derivatives have shown to be powerful cellular models for human biology. We work on leveraging them for a comparative approach by improving the generation, standardization and comparability of iPSCs from different primates and mammals. We use them to investigate the evolution of regulatory networks, the cross-species transferability of marker genes, human-specific features of atherosclerosis, and functional correlates of mammalian brain-size evolution.
Selected Publications:
Enard W. 2012. Functional primate genomics--leveraging the medical potential. J Mol Med (Berl) 90:471–480. doi:10.1007/s00109-012-0901-4
Wunderlich et al. 2014. Primate iPS cells as tools for evolutionary analyses. Stem Cell Res 12:622–629. doi:10.1016/j.scr.2014.02.001
Geuder et al. 2021. A non-invasive method to generate induced pluripotent stem cells from primate urine. Sci Rep 11:3516. doi:10.1038/s41598-021-82883-0
Edenhofer et al. 2024. Generation and characterization of inducible KRAB-dCas9 iPSCs from primates for cross-species CRISPRi. iScience 27:110090.
Jocher et al. 2026. Identification and comparison of orthologous cell types from primate embryoid bodies shows limits of marker gene transferability. Elife 14:RP105398. doi:10.7554/elife.105398.3
Examples of primate iPSCs generated in the Enard lab.
Humans are a remarkable species mainly due to the remarkable properties of their collective brains. Two properties of the brain that changed since the human lineage split from its common ancestor with chimpanzees is its size and its ability for speech. Understanding the molecular basis of these changes is interesting, but challenging. One way we approach it is studying the transcription factor FOXP2 and its two human-specific amino acid changes in mouse models. Another approach is a kind of Cross-species Association framework in which we correlate functional activity and genetic changes of candidate genes with changes in brain size across the mammalian tree.
Selected Publications:
Kliesmete Z, Wange LE, Vieth B, Esgleas M, Radmer J, Hülsmann M, Geuder J, Richter D, Ohnuki M, Götz M, Hellmann I, Enard W. 2023. Regulatory and coding sequences of TRNP1 co-evolve with brain size and cortical folding in mammals. Elife 12. doi:10.7554/eLife.83593
Enard et al. 2009. A humanized version of Foxp2 affects cortico-basal ganglia circuits in mice. Cell 137:961–971. doi:10.1016/j.cell.2009.03.041
Enard et al. 2002. Molecular evolution of FOXP2, a gene involved in speech and language. Nature 418:869–872. doi:10.1038/nature01025
Enard W. 2011. FOXP2 and the role of cortico-basal ganglia circuits in speech and language evolution. Curr Opin Neurobiol 21:415–424. doi:10.1016/j.conb.2011.04.008
Schreiweis et al. 2014. Humanized Foxp2 accelerates learning by enhancing transitions from declarative to procedural performance. Proc Natl Acad Sci U S A 111:14253–14258. doi:10.1073/pnas.1414542111
Bornschein et al. 2023. Functional dissection of two amino acid substitutions unique to the human FOXP2 protein. Sci Rep 13:3747. doi:10.1038/s41598-023-30663-3
Kliesmete et al. 2023. Regulatory and coding sequences of TRNP1 co-evolve with brain size and cortical folding in mammals. Elife 12. doi:10.7554/eLife.83593
A mouse model of humanized FOXP2 suggests medium spiny neurons of the striatum as a crucial hub for human speech evolution.
Bulk and single-cell RNA-seq are powerful tools for quantifying molecular and cellular phenotypes. We have benchmarked and developed RNA-seq protocols, are part of the Standards and Technology Working Group of the Human Cell Atlas, and contribute bulk and single-cell RNA-seq data generation to a wide range of local and international collaborations (see Wolfgang’s publication profile for examples).
Our main workhorse is currently prime-seq2, a powerful and efficient bulk RNA-seq protocol that reflects more than ten years of experience and continuous development. Its cost efficiency of less than €5 per sample makes it possible to profile substantially more conditions and replicates, thereby enabling new types of experimental designs.
One example is our recent study of the learning striatum, in which we compare gene expression across three stages of learning and multiple striatal regions in a total of 396 samples from 66 mice. This design allows us to identify where and when the largest changes in gene expression occur—conceptually similar to using hemodynamic or electrical signals as measures of brain activity—and subsequently to determine the neuronal and non-neuronal processes underlying these changes.
See protocols.io for a detailed, curated protocol, and feel free to reach out for advice and potential collaborations on bulk and single-cell RNA-seq.
Selected Publications:
Lousada et al. 2026. Expression profiling of the learning striatum. bioRxiv. doi:10.1101/2023.01.03.522560
Pförtner, Briem, et al. 2026. Increasing usable reads in RNA-seq protocols. iScience 29:116984. doi:10.1016/j.isci.2026.116984
Acera-Mateos et al 2026. Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues. Genome Biol 27:64.
Janssen et al. 2023. The effect of background noise and its removal on the analysis of single-cell expression data. Genome Biol 24:140. doi:10.1186/s13059-023-02978-x
Janjic et al.. 2022. Prime-seq, efficient and powerful bulk RNA sequencing. Genome Biol 23:88. doi:10.1186/s13059-022-02660-8
Bagnoli et al. 2018. Sensitive and powerful single-cell RNA sequencing using mcSCRB-seq. Nat Commun 9:2937. doi:10.1038/s41467-018-05347-6
Regev et al. 2017. The Human Cell Atlas. Elife 6. doi:10.7554/eLife.27041
Parekh S, Ziegenhain C, Vieth B, Enard W, Hellmann I. 2016. The impact of amplification on differential expression analyses by RNA-seq. Sci Rep 6:25533. doi:10.1038/srep25533
Ziegenhain et al.. 2017. Comparative Analysis of Single-Cell RNA Sequencing Methods. Mol Cell 65:631-643.e4. doi:10.1016/j.molcel.2017.01.023
Methods & Tools
© Carolin Bleese
- Prime-seq2 - an efficient, sensitive, and scalable bulk RNA-seq protocol optimized to maximize usable reads.
- mcSCRB-seq- a sensitive, UMI-based, plate-based method for single-cell RNA-seq.
- 10X scRNA-seq and multiome - high-throughput profiling of gene expression and chromatin accessibility at single-cell resolution.
- Primate CRISPRi- inducible gene repression in primate iPSCs for comparative functional studies of gene regulation.
- TAMED FISH - an image-analysis workflow for cell detection, spatial localization, and quantification of fluorescence in situ hybridization signals.
- Primate iPSCs- cross-species stem-cell models for studying the evolution of gene regulation and development.
Selected Publications
Pförtner, F., Briem, E., Enard, W., & Richter, D. (2026). Increasing usable reads in RNA-seq protocols. iScience, 29(8), 116984. https://doi.org/10.1016/j.isci.2026.116984
Jocher, J., Janssen, P., Vieth, B., Edenhofer, F. C., Dietl, T., Térmeg, A., Spurk, P., Geuder, J., Enard, W., & Hellmann, I. (2026). Identification and comparison of orthologous cell types from primate embryoid bodies shows limits of marker gene transferability. eLife, 14, RP105398. https://doi.org/10.7554/eLife.105398.3
Edenhofer, F. C., Térmeg, A., Ohnuki, M., Jocher, J., Kliesmete, Z., Briem, E., Hellmann, I., & Enard, W. (2024). Generation and characterization of inducible KRAB-dCas9 iPSCs from primates for cross-species CRISPRi. iScience, 27(6), 110090. https://doi.org/10.1016/j.isci.2024.110090
Kliesmete, Z., Wange, L. E., Vieth, B., Esgleas, M., Radmer, J., Hülsmann, M., Geuder, J., Richter, D., Ohnuki, M., Götz, M., Hellmann, I., & Enard, W. (2023). Regulatory and coding sequences of TRNP1 co-evolve with brain size and cortical folding in mammals. eLife, 12, e83593. https://doi.org/10.7554/eLife.83593
Janssen, P., Kliesmete, Z., Vieth, B., Adiconis, X., Simmons, S., Marshall, J., McCabe, C., Heyn, H., Levin, J. Z., Enard, W., & Hellmann, I. (2023). The effect of background noise and its removal on the analysis of single-cell expression data. Genome Biology, 24(1), 140. https://doi.org/10.1186/s13059-023-02978-x
Janjic, A., Wange, L. E., Bagnoli, J. W., Geuder, J., Nguyen, P., Richter, D., Vieth, B., Vick, B., Jeremias, I., Ziegenhain, C., Hellmann, I., & Enard, W. (2022). Prime-seq, efficient and powerful bulk RNA sequencing. Genome Biology, 23(1), 88. https://doi.org/10.1186/s13059-022-02660-8
Geuder, J., Wange, L. E., Janjic, A., Radmer, J., Janssen, P., Bagnoli, J. W., Müller, S., Kaul, A., Ohnuki, M., & Enard, W. (2021). A non-invasive method to generate induced pluripotent stem cells from primate urine. Scientific Reports, 11(1), 3516. https://doi.org/10.1038/s41598-021-82883-0
Ziegenhain, C., Vieth, B., Parekh, S., Reinius, B., Guillaumet-Adkins, A., Smets, M., Leonhardt, H., Heyn, H., Hellmann, I., & Enard, W. (2017). Comparative analysis of single-cell RNA sequencing methods. Molecular Cell, 65(4), 631–643.e4. https://doi.org/10.1016/j.molcel.2017.01.023
Schreiweis, C., Bornschein, U., Burguière, E., Kerimoglu, C., Schreiter, S., Dannemann, M., Goyal, S., Rea, E., French, C. A., Puliyadi, R., Groszer, M., Fisher, S. E., Mundry, R., Winter, C., Hevers, W., Pääbo, S., Enard, W., & Graybiel, A. M. (2014). Humanized Foxp2 accelerates learning by enhancing transitions from declarative to procedural performance. Proceedings of the National Academy of Sciences, 111(39), 14253–14258. https://doi.org/10.1073/pnas.1414542111
Enard, W., Gehre, S., Hammerschmidt, K., Hölter, S. M., Blass, T., Somel, M., Brückner, M. K., Schreiweis, C., Winter, C., Sohr, R., Becker, L., Wiebe, V., Nickel, B., Giger, T., Müller, U., Groszer, M., Adler, T., Aguilar, A., Bolle, I., Calzada-Wack, J., Dalke, C., Ehrhardt, N., Favor, J., Fuchs, H., Gailus-Durner, V., Hans, W., Hölzlwimmer, G., Javaheri, A., Kalaydjiev, S., Kallnik, M., Kling, E., Kunder, S., Moßbrugger, I., Naton, B., Racz, I., Rathkolb, B., Rozman, J., Schrewe, A., Busch, D. H., Graw, J., Ivandic, B., Klingenspor, M., Klopstock, T., Ollert, M., Quintanilla-Martinez, L., Schulz, H., Wolf, E., Wurst, W., Zimmer, A., Fisher, S. E., Morgenstern, R., Arendt, T., Hrabé de Angelis, M., Fischer, J., Schwarz, J., & Pääbo, S. (2009). A humanized version of Foxp2 affects cortico-basal ganglia circuits in mice. Cell, 137(5), 961–971. https://doi.org/10.1016/j.cell.2009.03.041
Enard, W., Przeworski, M., Fisher, S. E., Lai, C. S. L., Wiebe, V., Kitano, T., Monaco, A. P., & Pääbo, S. (2002). Molecular evolution of FOXP2, a gene involved in speech and language. Nature, 418(6900), 869–872. https://doi.org/10.1038/nature01025
Enard, W., Khaitovich, P., Klose, J., Zöllner, S., Heissig, F., Giavalisco, P., Nieselt-Struwe, K., Muchmore, E., Varki, A., Ravid, R., Doxiadis, G. M., Bontrop, R. E., & Pääbo, S. (2002). Intra- and interspecific variation in primate gene expression patterns. Science, 296(5566), 340–343. https://doi.org/10.1126/science.1068996
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