Left-right lateralization is an important organizing principle of the human brain which is not a current focus of HBP research. One prominently lateralized anatomical and functional network underlies the uniquely human ability to speak and understand language. A lack of brain lateralization has been associated with variation in human cognitive abilities important to language, and also with susceptibility to neurocognitive disorders including language impairment, dyslexia, autism and schizophrenia. The genetic basis of human brain lateralization is unknown, while links between lateralized anatomy and function are poorly understood. It is likely that genes involved in lateralization, both developmentally and during adult function, contain variants in the population that influence cognitive performance and neurocognitive disorders. We are generating transcriptomic data on lateralized gene expression in the embryonic and adult human brain. We recently identified, for the first time, sets of neuronal genes in the healthy adult brain that are expressed at different levels in the left and right temporal cerebral cortex (crucial for the language network). Here we propose a multi-level and integrated analysis of brain lateralization for language: I. Develop improved methods to reliably and automatically measure individual differences in lateralization of the language network in large numbers of participants, for anatomy, resting state intrinsic connectivity, and task-related function. The language cortex is a variable region for which current automated methods do not perform optimally, yet automated methods are essential for achieving large datasets that are statistically powered for for genetic studies. It is essential to understand human brain diversity, as well as researching the average brain which is the focus of most HBP activity. II. Apply the methods in brain imaging datasets having genetic data available, for the purposes of association and rare variant analysis followed by integrated genome-level analysis with transcriptomic (lateralized gene expression) data and genomic gene-set analysis. These combinatorial analyses go beyond standard genome-wide association scanning. Rather, the genomic data will be utilized to merge multiple genetic signals, informed by gene expression data and gene function data, in order to increase statistical power. III. Relate the gene sets arising from step II to human cognitive variability linked to reading and language, and susceptibility to neurocognitive disorders. Again, evidence-based combinations of genetic variants, constructed over many genes, will be investigated. Pinpointing shared genetic effects on lateralization and cognition would discriminate causal relations from mere correlation. Outcomes from this research program will include improved technology for automated analysis of large numbers of brain scans, and possible definition of susceptibility factors for important subtypes of impaired cognition.

This project investigated the language environments and early language development of children in multiple Indigenous communities and multiple urban Western communities (in the US and Europe). The datasets created feature carefully annotated language clips from day-long home recordings to examine early sound and word development in two unrelated, horticulturalist communities (Tseltal; Southern Mexico and Rossel; Papua New Guinea). The emerging picture from this work is that the human mind is rather robust in its ability to learn language across diverse cultural and linguistic environments, laying the groundwork for exciting new comparative research in the future.

Viewing language as a complex cultural evolutionary system has greatly advanced our understanding of some fundamental questions concerning its biological bases, cognitive implementation, universal tendencies and the spatio-temporal patterning of linguistic diversity. Genetic biasing represents one important but understudied factor, influencing the diachronic trajectory of language change by affecting language transmission across generations (Dediu & Ladd, 2007; Ladd et al., 2008; Dediu, 2011b). This project will advance our understanding of the nature, mechanisms and consequences of such biases affecting language and, in particular, speech. The project builds on my previous ground-breaking work, by focusing on three main directions: (1) computational modelling of genetically biased language transmission (Dediu, 2008, 2009), (2) statistical and evolutionary analyses of typological and genetic diversities (Dediu, 2011b; Dediu & Ladd, 2007), and (3) the collection of data on vocal tract variation and its effects on speech. Direction (1) will help understand the types of biases and the social, linguistic and demographic conditions that lead to genetically biased language transmission. Moreover, it will highlight the "traces" these processes leave, allowing their identification in real data. Direction (2) will apply advanced statistical and evolutionary techniques to identifying aspects of language and the human genome that might be involved in biased cultural transmission. Direction (3) will involve primary data collection of vocal tract parameters from key populations and individuals, experimental articulatory phonetic techniques, and computer models of the vocal tract used to link patterns of vocal tract and speech variation. We will also conduct an extensive review of the various literatures (phonetics, dentistry, medical genetics, anthropology...) concerning vocal tract variation, its genetic bases and effects on speech. These findings will open new directions for exploring language evolution and change as well as linguistic universals and variation. The project will also develop new quantitative methods for studying language.

Methanol and other ‘1-carbon molecules’ are ideal sources for the production of biochemicals and biofuels. Unfortunately, microorganisms suitable for biotechnological production, such as Escherichia coli, cannot grow on these sources. The researcher will engineer possible genetic mutations in E. coli for eating one-carbon substrates, and learn which mutations are important.

Cell polarization is a fundamental biological process implicated in almost every step of multicellular development. Polarization of epithelial cells enables functional asymmetry between the apical (external facing) and basolateral (internal facing) membranes. Hepatocytes, the epithelial cells that form the liver parenchyma, are uniquely polarized to contain multiple apical and basal membranes. During liver development, the apical membranes of adjacent hepatocytes form small tubular lumina, termed bile canaliculi (BC), which connect into a complex three-dimensional network to mediate the secretion of bile. Despite its clear relevance for liver physiology, the molecular mechanisms that underlie the anisotropic (geometrically asymmetric) elongation of the apical lumen into tubular BC remain to be elucidated. In this interdisciplinary project, I will use a novel primary mouse hepatoblast culture system that recapitulates key features of the establishment of hepatocyte polarity during liver development. State-of-the-art microscopic techniques will be employed to perform a detailed morphological characterization of the hepatocyte apical membrane. Furthermore, I will use biophysical manipulation and optogenetic tools to understand how the actomyosin cytoskeleton, junctional complexes, and endosomal system co-operate to drive anisotropic BC growth. Ultimately, this project will illuminate the mechanisms that underpin the unique polarization of hepatocytes.