Mouse models of human evolution

A Positively Selected MAGEE2 LoF Allele Is Associated with Sexual Dimorphism in Human Brain Size and Shows Similar Phenotypes in Magee2 Null Mice

A nonsense allele at rs1343879 in human MAGEE2 on chromosome X has previously been reported as a strong candidate for positive selection in East Asia. This premature stop codon causing ∼80% protein truncation is characterized by a striking geographical pattern of high population differentiation: common in Asia and the Americas (up to 84% in the 1000 Genomes Project East Asians) but rare elsewhere. Here, we generated a Magee2 mouse knockout mimicking the human loss-of-function mutation to study its functional consequences. The Magee2 null mice did not exhibit gross abnormalities apart from enlarged brain structures (13% increased total brain area, P = 0.0022) in hemizygous males. The area of the granular retrosplenial cortex responsible for memory, navigation, and spatial information processing was the most severely affected, exhibiting an enlargement of 34% (P = 3.4×10-6). The brain size in homozygous females showed the opposite trend of reduced brain size, although this did not reach statistical significance. With these insights, we performed human association analyses between brain size measurements and rs1343879 genotypes in 141 Chinese volunteers with brain MRI scans, replicating the sexual dimorphism seen in the knockout mouse model. The derived stop gain allele was significantly associated with a larger volume of gray matter in males (P = 0.00094), and smaller volumes of gray (P = 0.00021) and white (P = 0.0015) matter in females. It is unclear whether or not the observed neuroanatomical phenotypes affect behavior or cognition, but it might have been the driving force underlying the positive selection in humans.

FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations

We present a new method, Fine-Mapping of Adaptive Variation (FineMAV), which combines population differentiation, derived allele frequency, and molecular functionality to prioritize positively selected candidate variants for functional follow-up. We calibrate and test FineMAV using eight experimentally validated "gold standard" positively selected variants and simulations. FineMAV has good sensitivity and a low false discovery rate. Applying FineMAV to the 1000 Genomes Project Phase 3 SNP dataset, we report many novel selected variants, including ones in TGM3 and PRSS53 associated with hair phenotypes that we validate using available independent data. FineMAV is widely applicable to sequence data from both human and other species.

The Molecular Basis of Human Brain Evolution

Humans are a remarkable species, especially because of the remarkable properties of their brain. Since the split from the chimpanzee lineage, the human brain has increased three-fold in size and has acquired abilities for vocal learning, language and intense cooperation. To better understand the molecular basis of these changes is of great biological and biomedical interest. However, all the about 16 million fixed genetic changes that occurred during human evolution are fully correlated with all molecular, cellular, anatomical and behavioral changes that occurred during this time. Hence, as humans and chimpanzees cannot be crossed or genetically manipulated, no direct evidence for linking particular genetic and molecular changes to human brain evolution can be obtained. Here, I sketch a framework how indirect evidence can be obtained and review findings related to the molecular basis of human cognition, vocal learning and brain size. In particular, I discuss how a comprehensive comparative approach, leveraging cellular systems and genomic technologies, could inform the evolution of our brain in the future.

Evolution of language: Lessons from the genome

The post-genomic era is an exciting time for researchers interested in the biology of speech and language. Substantive advances in molecular methodologies have opened up entire vistas of investigation that were not previously possible, or in some cases even imagined. Speculations concerning the origins of human cognitive traits are being transformed into empirically addressable questions, generating specific hypotheses that can be explicitly tested using data collected from both the natural world and experimental settings. In this article, I discuss a number of promising lines of research in this area. For example, the field has begun to identify genes implicated in speech and language skills, including not just disorders but also the normal range of abilities. Such genes provide powerful entry points for gaining insights into neural bases and evolutionary origins, using sophisticated experimental tools from molecular neuroscience and developmental neurobiology. At the same time, sequencing of ancient hominin genomes is giving us an unprecedented view of the molecular genetic changes that have occurred during the evolution of our species. Synthesis of data from these complementary sources offers an opportunity to robustly evaluate alternative accounts of language evolution. Of course, this endeavour remains challenging on many fronts, as I also highlight in the article. Nonetheless, such an integrated approach holds great potential for untangling the complexities of the capacities that make us human.

Shortcomings of Animal Models and the Rise of Engineered Human Cardiac Tissue

We provide here an historical context of how studies utilizing engineered human cardiac muscle can complement and in some cases substitute animal and cell models for studies of disease and drug testing. We give an overview of the development of animal models and discuss the ability of novel human tissue models to overcome limited predictive power of cell culture and animal models in studies of drug efficacy and safety. The in vitro generation of cardiac tissue is discussed in the context of state of the art in the field. Finally we describe the assembly of multitissue platforms for more accurate representation of integrated human cardiac physiology and consider the advantages of in silico drug trials to augment our ability to predict drug-drug and organ-organ interactions in humans.

Mice carrying a human GLUD2 gene recapitulate aspects of human transcriptome and metabolome development

Whereas all mammals have one glutamate dehydrogenase gene (GLUD1), humans and apes carry an additional gene (GLUD2), which encodes an enzyme with distinct biochemical properties. We inserted a bacterial artificial chromosome containing the human GLUD2 gene into mice and analyzed the resulting changes in the transcriptome and metabolome during postnatal brain development. Effects were most pronounced early postnatally, and predominantly genes involved in neuronal development were affected. Remarkably, the effects in the transgenic mice partially parallel the transcriptome and metabolome differences seen between humans and macaques analyzed. Notably, the introduction of GLUD2 did not affect glutamate levels in mice, consistent with observations in the primates. Instead, the metabolic effects of GLUD2 center on the tricarboxylic acid cycle, suggesting that GLUD2 affects carbon flux during early brain development, possibly supporting lipid biosynthesis.

Genomic approaches to studying human-specific developmental traits

Changes in developmental regulatory programs drive both disease and phenotypic differences among species. Linking human-specific traits to alterations in development is challenging, because we have lacked the tools to assay and manipulate regulatory networks in human and primate embryonic cells. This field was transformed by the sequencing of hundreds of genomes – human and non-human – that can be compared to discover the regulatory machinery of genes involved in human development. This approach has identified thousands of human-specific genome alterations in developmental genes and their regulatory regions. With recent advances in stem cell techniques, genome engineering, and genomics, we can now test these sequences for effects on developmental gene regulation and downstream phenotypes in human cells and tissues.

A humanized version of Foxp2 does not affect ultrasonic vocalization in adult mice

The transcription factor FOXP2 has been linked to severe speech and language impairments in humans. An analysis of the evolution of the FOXP2 gene has identified two amino acid substitutions that became fixed after the split of the human and chimpanzee lineages. Studying the functional consequences of these two substitutions in the endogenous Foxp2 gene of mice showed alterations in dopamine levels, striatal synaptic plasticity, neuronal morphology and cortico-striatal-dependent learning. In addition, ultrasonic vocalizations (USVs) of pups had a significantly lower average pitch than control littermates. To which degree adult USVs would be affected in mice carrying the 'humanized' Foxp2 variant remained unclear. In this study, we analyzed USVs of 68 adult male mice uttered during repeated courtship encounters with different females. Mice carrying the Foxp2(hum/hum) allele did not differ significantly in the number of call elements, their element structure or in their element composition from control littermates. We conclude that neither the structure nor the usage of USVs in adult mice is affected by the two amino acid substitutions that occurred in FOXP2 during human evolution. The reported effect for pup vocalization thus appears to be transient. These results are in line with accumulating evidence that mouse USVs are hardly influenced by vocal learning. Hence, the function and evolution of genes that are necessary, but not sufficient for vocal learning in humans, must be either studied at a different phenotypic level in mice or in other organisms.

Mouse Models as Predictors of Human Responses: Evolutionary Medicine

Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.