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Demographics of Retinal Nerve Cell Populations

视网膜神经细胞群的人口统计学

基本信息

批准号：
9485757
负责人：
BENJAMIN E REESE
金额：
$ 1.43万
依托单位：
UNIVERSITY OF CALIFORNIA SANTA BARBARA
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-01-01 至 2019-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9485757
关键词：
Address Afferent Neurons Amacrine Cells Architecture Biological Assay Biological Models Candidate Disease Gene Cell Count Cell Death Cell Density Cells Data Data Set Dendrites Development Developmental Process Distal Electroporation Foundations Ganglion Cell Layer Gene Expression Genes Genetic Genetic Determinism Genomics Growth Harvest Heritability In Situ Hybridization In Vitro Inbred Strains Mice Inner Nuclear Layer Knock-out Knockout Mice Lobular Luciferases Maps Measures Mediating Messenger RNA Molecular Molecular Profiling Mono-S Morphology Mosaicism Mouse Strains Mus Neuronal Differentiation Neurons Output Pattern Plasmids Population Population Dynamics Positioning Attribute Quantitative Trait Loci Recombinant Inbred Strain Recombinants Regenerative Medicine Regulation Research Research Proposals Retina Retinal Retinal Diseases Role Sampling Source Specificity Statistical Data Interpretation Stratification Surface Synapses Territoriality Testing Tissues Transcript Variant cell type cholinergic demographics developmental disease genetic variant horizontal cell knockout gene knowledge base nervous system disorder neuronal cell body overexpression programs public health relevance relating to nervous system response retinal neuron trait transcription factor transcriptome

项目摘要

DESCRIPTION (provided by applicant): Populations of neurons vary in their demographics: They differ in their absolute numbers, in their intercellular spacing and the patterning this produces, in their degree of dendritic overlap and its regulation, and in their synaptic connectivity and the convergence ratios associated with their afferent neurons. The present research program has been addressing the causal relationships associated with such neuronal population dynamics, using the retina as a model system and working with a panel of twenty-six genetically distinct recombinant inbred (RI) mouse strains. Neuron number has been shown to vary considerably across these strains of mice, for twelve different classes of retinal neuron, and this variation maps to discrete genomic loci (quantitative trait loci, or QTL) for each cell type, showing minimal evidence for genomic co-regulation. The genetic sources of this variation in neuron number will be defined, for each cell type, and the developmental roles of these genes modulating cell number will be identified. Independent of neuron number, neurons vary in other histotypical features across these RI strains, including the orderliness by which they space themselves apart within a layer. The population of horizontal cells is one such example, where variation in the orderliness of their patterning maps to two narrow genomic loci. Causal genes and their variants at these loci will be pursued, and comparable spatial statistical analysis will e conducted for the other cell types to map QTL in pursuit of the genetic determinants of neuronal spacing. The consequence of such independent variation in the number of afferent and target neurons upon dendritic differentiation will also be examined, using the AII amacrine cell to explore the unique independent control of its lobular versus dendritic growth. Finally, a role for the transcription factor Sox2 in cholinergic amacrine cells has recently been demonstrated, causing a mis- positioning of these amacrine cells between the inner nuclear layer and ganglion cell layer, and a conversion of their mono-stratifying dendrites into a bi-stratifying morphology. The role of Sox2 will be further explored to identify the downstream genes responsible for these altered cholinergic amacrine cell traits, by transcriptome- profiling of purified cholinergic amacrine cells from Sox2-deficient versus control retinas. The present research proposal will thereby identify the genetic determinants and intercellular interactions that underlie the demographic features of neuronal populations in the retina, clarifying our understanding of retinal development, as well as identifying genetic variants that may contribute to retinal disease.