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Biology subjects

Wong, E.

Publications and source records attributed to Wong, E..

5 recordsLinked to original sources

Machine Learning Reveals Modules of Economic Behavior from Foraging Mice

Complex ethological behaviors could be constructed from modules that are discrete functional units of behavior with a genetic basis. Here, we test this idea for foraging, and develop a paradigm to dissect foraging patterns in mice. We uncover discrete behavioral modules linked to round trip excursions from the home. Machine learning reveals 59 modules across different genetic backgrounds and ages. Different modules develop at different ages and are linked to different aspects of economic behavior, including memory, reward, risk and effort responses. Crosses of distant mouse strains reveal that parental and genetic effects shape foraging differently, and parental effects grow stronger with age. Specific behavioral modules, genes and pathways are found to be sensitive to parental effects. One candidate gene, Magel2, is linked to Prader-Willi Syndrome and shaped the expression of discrete modules in an age-dependent manner. Our results reveal building blocks for normal and abnormal economic behavior patterns.\n\nHIGHLIGHTSO_LIIdentification of 59 economic behavior modules underlying foraging\nC_LIO_LIDiscrete modules are linked to memory, reward, risk and effort responses\nC_LIO_LIGenetic and parental effects shape foraging by changing module expression\nC_LIO_LIMagel2, a Prader-Willi Syndrome gene, affects specific modules at specific ages\nC_LI

neuroscience

A Highly Efficient and Faithful MDS Patient-Derived Xenotransplantation Model for Pre-Clinical Studies

Comprehensive preclinical studies of Myelodysplastic Syndromes (MDS) have been elusive due to limited ability of MDS stem cells to engraft current immunodeficient murine hosts. We developed a novel MDS patient-derived xenotransplantation model in cytokine-humanized immunodeficient \"MISTRG\" mice that for the first time provides efficient and faithful disease representation across all MDS subtypes. MISTRG MDS patient-derived xenografts (PDX) reproduce patients' dysplastic morphology with multi-lineage representation, including erythro- and megakaryopoiesis. MISTRG MDS-PDX replicate the original sample's genetic complexity and can be propagated via serial transplantation. MISTRG MDS-PDX demonstrate the cytotoxic and differentiation potential of targeted therapeutics providing superior readouts of drug mechanism of action and therapeutic efficacy. Physiologic humanization of the hematopoietic stem cell niche proves critical to MDS stem cell propagation and function in vivo. The MISTRG MDS-PDX model opens novel avenues of research and long-awaited opportunities in MDS research.

cancer biology

Cardiac directed differentiation using small molecule Wnt modulation at single-cell resolution

Differentiation into diverse cell lineages requires the orchestration of gene regulatory networks guiding diverse cell fate choices. Utilizing human pluripotent stem cells, we measured expression dynamics of 17,718 genes from 43,168 cells across five time points over a thirty day time-course of in vitro cardiac-directed differentiation. Unsupervised clustering and lineage prediction algorithms were used to map fate choices and transcriptional networks underlying cardiac differentiation. We leveraged this resource to identify strategies for controlling in vitro differentiation as it occurs in vivo. HOPX, a non-DNA binding homeodomain protein essential for heart development in vivo was identified as dys-regulated in in vitro derived cardiomyocytes. Utilizing genetic gain and loss of function approaches, we dissect the transcriptional complexity of the HOPX locus and identify the requirement of hypertrophic signaling for HOPX transcription in hPSC-derived cardiomyocytes. This work provides a single cell dissection of the transcriptional landscape of cardiac differentiation for broad applications of stem cells in cardiovascular biology.

developmental biology

Allelic Differentiation Of Complex Trait Loci Across Human Populations

How genetic variation contributes to phenotypic variation is a central question in genetics. Association signals for a complex trait are found throughout the majority of the genome suggesting much of the genome is under some degree of genetic constraint. Here, we develop a intraspecific population genetics approach to define a measure of population structure for each single nucleotide polymorphism (SNP). Using this approach, we test for evidence of stabilizing selection at complex traits and pleiotropic loci arising from the evolutionary history of 47 complex traits and common diseases. Our approach allowed us to identify traits and regions under stabilizing selection towards both global and subpopulation optima. Strongest depletion of allelic diversity was found at disease loci, indicating stabilizing selection has acted on these phenotypes in all subpopulations. Pleiotropic loci predominantly displayed evidence of stabilizing selection, often contributed to multiple disease risks, and sometimes also affected non-disease traits such as height. Risk alleles at pleiotropic disease loci displayed a more consistent direction of effect than expected by chance suggesting that stabilizing selection acting on pleiotropic loci is amplified through multiple disease phenotypes.

evolutionary biology

The human functional genome defined by genetic diversity

Large scale efforts to sequence whole human genomes provide extensive data on the non-coding portion of the genome. We used variation information from 11,257 human genomes to describe the spectrum of sequence conservation in the population. We established the genome-wide variability for each nucleotide in the context of the surrounding sequence in order to identify departure from expectation at the population level (context-dependent conservation). We characterized the population diversity for functional elements in the genome and identified the coordination of conserved sequences of distal and cis enhancers, chromatin marks, promoters, coding and intronic regions. The most context-dependent conserved regions of the genome are associated with unique functional annotations and a genomic organization that spreads up to one megabase. Importantly, these regions are enriched by over 100-fold of non-coding pathogenic variants. This analysis of human genetic diversity thus provides a detailed view of sequence conservation, functional constraint and genomic organization of the human genome. Specifically, it identifies highly conserved non-coding sequences that are not captured by analysis of interspecies conservation and are greatly enriched in disease variants.

genomics